To match bone marrow donors and recipients, ask about grandma

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To match bone marrow donors and recipients, ask about grandma

Bone marrow harvest

Photo by Chad McNeeley

Asking bone marrow donors about their grandparents’ ancestry may help match donors to the appropriate recipients, according to research published in PLOS ONE.

Investigators found that when donors were self-reporting their race/ethnicity and included information on their grandparents’ ancestry, their responses often matched their genetics better than when they simply selected from standard race/ethnicity categories.

The investigators said these results show that more research is needed to refine methods for collecting and interpreting information on race/ethnicity for medical purposes.

“In medicine, we’ve been under the assumption that it’s just a matter of presenting people with the right check boxes,” said Jill Hollenbach, PhD, of the University of California, San Francisco. “It turns out that it’s much more complex than that.”

She and her colleagues noted that identifying a 10/10 human leukocyte antigen (HLA) match in the National Marrow Donor Program’s Be The Match Registry can be difficult because most of the donors submitted samples at a time when genotyping was much less advanced than it is today.

To find likely matches to pursue, the registry uses bioinformatics to weed out the donors unlikely to have matching HLA genes. Although HLA genes are highly variable, certain variations are found at higher frequencies in some regions of the world than others.

A patient with geographic ancestry in East Asia, for example, is more likely to have the same HLA variation as someone with origins in East Asia, rather than someone with European ancestry.

To obtain such information, most medical facilities use the patients’ race/ethnicity self-identification as a proxy. This can be challenging for people who trace their ancestry to multiple origins.

“The United States census uses a “check all that apply” technique, which is OK, but we want to try to get a little more refined to improve our matching efficiency,” said study author Martin Maiers, director of Bioinformatics Research at the Be The Match Registry.

To assess the extent to which different means of self-identification correspond to genetic ancestry, the investigators recruited 1752 potential donors from the Be The Match Registry.

The team sent participants a questionnaire with multiple measures of self-identification, including race/ethnicity and geographic ancestry, and asked participants to assign geographic ancestry to their grandparents. Participants also submitted cheek swabs as DNA samples.

By analyzing the cheek swabs, the investigators genotyped 93 ancestry informative markers to identify the participants’ genetic ancestry. This revealed a strong correlation between the ancestry markers and HLA genes.

Unfortunately, no measure of self-identification showed complete correspondence with a donor’s genetic ancestry. However, information about the geographic origins of the donors’ grandparents corresponded most closely with genetics, particularly for participants with ancestry from multiple continents.

“The conventional wisdom of the last decade or two has been that race is a social construct,” Dr Hollenbach said. “That’s true, but race is also part of the language of self-identification in [the US]. Let’s understand how these different forms of self-identification and genetic ancestry intersect to improve transplant matching for people of all ancestral backgrounds.”

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Bone marrow harvest

Photo by Chad McNeeley

Asking bone marrow donors about their grandparents’ ancestry may help match donors to the appropriate recipients, according to research published in PLOS ONE.

Investigators found that when donors were self-reporting their race/ethnicity and included information on their grandparents’ ancestry, their responses often matched their genetics better than when they simply selected from standard race/ethnicity categories.

The investigators said these results show that more research is needed to refine methods for collecting and interpreting information on race/ethnicity for medical purposes.

“In medicine, we’ve been under the assumption that it’s just a matter of presenting people with the right check boxes,” said Jill Hollenbach, PhD, of the University of California, San Francisco. “It turns out that it’s much more complex than that.”

She and her colleagues noted that identifying a 10/10 human leukocyte antigen (HLA) match in the National Marrow Donor Program’s Be The Match Registry can be difficult because most of the donors submitted samples at a time when genotyping was much less advanced than it is today.

To find likely matches to pursue, the registry uses bioinformatics to weed out the donors unlikely to have matching HLA genes. Although HLA genes are highly variable, certain variations are found at higher frequencies in some regions of the world than others.

A patient with geographic ancestry in East Asia, for example, is more likely to have the same HLA variation as someone with origins in East Asia, rather than someone with European ancestry.

To obtain such information, most medical facilities use the patients’ race/ethnicity self-identification as a proxy. This can be challenging for people who trace their ancestry to multiple origins.

“The United States census uses a “check all that apply” technique, which is OK, but we want to try to get a little more refined to improve our matching efficiency,” said study author Martin Maiers, director of Bioinformatics Research at the Be The Match Registry.

To assess the extent to which different means of self-identification correspond to genetic ancestry, the investigators recruited 1752 potential donors from the Be The Match Registry.

The team sent participants a questionnaire with multiple measures of self-identification, including race/ethnicity and geographic ancestry, and asked participants to assign geographic ancestry to their grandparents. Participants also submitted cheek swabs as DNA samples.

By analyzing the cheek swabs, the investigators genotyped 93 ancestry informative markers to identify the participants’ genetic ancestry. This revealed a strong correlation between the ancestry markers and HLA genes.

Unfortunately, no measure of self-identification showed complete correspondence with a donor’s genetic ancestry. However, information about the geographic origins of the donors’ grandparents corresponded most closely with genetics, particularly for participants with ancestry from multiple continents.

“The conventional wisdom of the last decade or two has been that race is a social construct,” Dr Hollenbach said. “That’s true, but race is also part of the language of self-identification in [the US]. Let’s understand how these different forms of self-identification and genetic ancestry intersect to improve transplant matching for people of all ancestral backgrounds.”

Bone marrow harvest

Photo by Chad McNeeley

Asking bone marrow donors about their grandparents’ ancestry may help match donors to the appropriate recipients, according to research published in PLOS ONE.

Investigators found that when donors were self-reporting their race/ethnicity and included information on their grandparents’ ancestry, their responses often matched their genetics better than when they simply selected from standard race/ethnicity categories.

The investigators said these results show that more research is needed to refine methods for collecting and interpreting information on race/ethnicity for medical purposes.

“In medicine, we’ve been under the assumption that it’s just a matter of presenting people with the right check boxes,” said Jill Hollenbach, PhD, of the University of California, San Francisco. “It turns out that it’s much more complex than that.”

She and her colleagues noted that identifying a 10/10 human leukocyte antigen (HLA) match in the National Marrow Donor Program’s Be The Match Registry can be difficult because most of the donors submitted samples at a time when genotyping was much less advanced than it is today.

To find likely matches to pursue, the registry uses bioinformatics to weed out the donors unlikely to have matching HLA genes. Although HLA genes are highly variable, certain variations are found at higher frequencies in some regions of the world than others.

A patient with geographic ancestry in East Asia, for example, is more likely to have the same HLA variation as someone with origins in East Asia, rather than someone with European ancestry.

To obtain such information, most medical facilities use the patients’ race/ethnicity self-identification as a proxy. This can be challenging for people who trace their ancestry to multiple origins.

“The United States census uses a “check all that apply” technique, which is OK, but we want to try to get a little more refined to improve our matching efficiency,” said study author Martin Maiers, director of Bioinformatics Research at the Be The Match Registry.

To assess the extent to which different means of self-identification correspond to genetic ancestry, the investigators recruited 1752 potential donors from the Be The Match Registry.

The team sent participants a questionnaire with multiple measures of self-identification, including race/ethnicity and geographic ancestry, and asked participants to assign geographic ancestry to their grandparents. Participants also submitted cheek swabs as DNA samples.

By analyzing the cheek swabs, the investigators genotyped 93 ancestry informative markers to identify the participants’ genetic ancestry. This revealed a strong correlation between the ancestry markers and HLA genes.

Unfortunately, no measure of self-identification showed complete correspondence with a donor’s genetic ancestry. However, information about the geographic origins of the donors’ grandparents corresponded most closely with genetics, particularly for participants with ancestry from multiple continents.

“The conventional wisdom of the last decade or two has been that race is a social construct,” Dr Hollenbach said. “That’s true, but race is also part of the language of self-identification in [the US]. Let’s understand how these different forms of self-identification and genetic ancestry intersect to improve transplant matching for people of all ancestral backgrounds.”

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Blood-cleansing device on the way to the clinic, team says

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Blood-cleansing device on the way to the clinic, team says

Red blood cells positive

for Staphylococcus infection

Photo by Bill Branson

Last year, researchers reported promising preclinical results with a device that can treat sepsis by mimicking the human spleen. The device filtered pathogens and toxins from the blood by passing it through a dialysis-like circuit.

Now, the researchers have developed a new, more streamlined device that, they believe, is more likely to translate to the clinic. The new device also synergizes with conventional antibiotic therapies.

The team described this device in Biomaterials.

“The inflammatory cascade that leads to sepsis is triggered by pathogens and, specifically, by the toxins they release,” said study author Donald Ingber, MD, PhD, of the Wyss Institute for Biologically Inspired Engineering at Harvard University in Cambridge, Massachusetts.

“Thus, the most effective strategy is to treat with the best antibiotics you can muster, while also removing the toxins and remaining pathogens from the patient’s blood as quickly as possible.”

How the device works

The researchers say their new blood-cleansing approach can be completed quickly, without even identifying the infectious agent. This is because the device uses a proprietary pathogen-capturing agent, known as FcMBL, that binds all types of live and dead infectious microbes, including bacteria, fungi, viruses, and the toxins they release.

FcMBL is a genetically engineered blood protein inspired by a naturally occurring human molecule called mannose binding lectin (MBL). MBL is found in the innate immune system and binds to toxic invaders, marking them for capture by immune cells in the spleen.

The researchers’ original device concept was similar to how a dialysis machine works. Infected blood in an animal, or potentially one day in a patient, is flowed from one vein through catheters to the device.

There, FcMBL-coated magnetic beads are added to the blood, and the bead-bound pathogens are extracted from the circulating blood by magnets within the device before the cleansed blood is returned to the body through another vein.

The new device removes the complexity, regulatory challenges, and cost associated with the magnetic beads and microfluidic architecture of its predecessor. But it still uses the FcMBL protein to bind to pathogens and toxins.

The new system uses hollow fiber filters similar to those currently used in hemodialysis, but the inner walls of these filters are coated with FcMBL protein to remove pathogens from circulating blood.

Test results

In in vitro tests with human blood, the device reduced the number of Gram-negative bacteria (Escherichia coli), Gram-positive bacteria (Staphylococcus aureus), fungi (Candida albicans), and lipopolysaccharide-endotoxins by 90% to 99%.

In tests with rats, the device reduced levels of circulating pathogens and endotoxins by more than 99%, and it prevented pathogen engraftment and inflammatory cell recruitment in the spleen, lung, liver, and kidney.

The researchers also tested the device in combination with bacteriocidal antibiotics in rats. The antibiotics prompted a “major increase” in the release of microbial fragments, or pathogen-associated molecular patterns (PAMPs).

The device could remove PAMPs from the blood within 2 hours, but high levels of PAMPs remained in rats treated with antibiotics alone.

The researchers said PAMP removal reduced organ pathogen and endotoxin loads, suppressed inflammatory responses, and resulted in more stable vital signs.

“Using the device, alone or alongside antibiotics, we can quickly bring blood back to normal conditions, curtailing an inflammatory response rather than exacerbating it,” said Tohid Fatanat Didar, PhD, of the Wyss Institute.

“If all goes well, physicians will someday be able to use the device in tandem with standard antibiotic treatments to deliver a one-two punch to pathogens, synergistically killing and cleansing all live and dead invaders from the bloodstream.”

 

 

As the device has proven effective in small animal experiments, the researchers are planning to move to large animal studies. They must demonstrate proof-of-concept in these models before advancing to clinical trials.

“Our goal is to see this move out of the lab and into hospitals, as well as onto the battlefield,” Dr Ingber said, “where it can save lives within years rather than decades.”

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Red blood cells positive

for Staphylococcus infection

Photo by Bill Branson

Last year, researchers reported promising preclinical results with a device that can treat sepsis by mimicking the human spleen. The device filtered pathogens and toxins from the blood by passing it through a dialysis-like circuit.

Now, the researchers have developed a new, more streamlined device that, they believe, is more likely to translate to the clinic. The new device also synergizes with conventional antibiotic therapies.

The team described this device in Biomaterials.

“The inflammatory cascade that leads to sepsis is triggered by pathogens and, specifically, by the toxins they release,” said study author Donald Ingber, MD, PhD, of the Wyss Institute for Biologically Inspired Engineering at Harvard University in Cambridge, Massachusetts.

“Thus, the most effective strategy is to treat with the best antibiotics you can muster, while also removing the toxins and remaining pathogens from the patient’s blood as quickly as possible.”

How the device works

The researchers say their new blood-cleansing approach can be completed quickly, without even identifying the infectious agent. This is because the device uses a proprietary pathogen-capturing agent, known as FcMBL, that binds all types of live and dead infectious microbes, including bacteria, fungi, viruses, and the toxins they release.

FcMBL is a genetically engineered blood protein inspired by a naturally occurring human molecule called mannose binding lectin (MBL). MBL is found in the innate immune system and binds to toxic invaders, marking them for capture by immune cells in the spleen.

The researchers’ original device concept was similar to how a dialysis machine works. Infected blood in an animal, or potentially one day in a patient, is flowed from one vein through catheters to the device.

There, FcMBL-coated magnetic beads are added to the blood, and the bead-bound pathogens are extracted from the circulating blood by magnets within the device before the cleansed blood is returned to the body through another vein.

The new device removes the complexity, regulatory challenges, and cost associated with the magnetic beads and microfluidic architecture of its predecessor. But it still uses the FcMBL protein to bind to pathogens and toxins.

The new system uses hollow fiber filters similar to those currently used in hemodialysis, but the inner walls of these filters are coated with FcMBL protein to remove pathogens from circulating blood.

Test results

In in vitro tests with human blood, the device reduced the number of Gram-negative bacteria (Escherichia coli), Gram-positive bacteria (Staphylococcus aureus), fungi (Candida albicans), and lipopolysaccharide-endotoxins by 90% to 99%.

In tests with rats, the device reduced levels of circulating pathogens and endotoxins by more than 99%, and it prevented pathogen engraftment and inflammatory cell recruitment in the spleen, lung, liver, and kidney.

The researchers also tested the device in combination with bacteriocidal antibiotics in rats. The antibiotics prompted a “major increase” in the release of microbial fragments, or pathogen-associated molecular patterns (PAMPs).

The device could remove PAMPs from the blood within 2 hours, but high levels of PAMPs remained in rats treated with antibiotics alone.

The researchers said PAMP removal reduced organ pathogen and endotoxin loads, suppressed inflammatory responses, and resulted in more stable vital signs.

“Using the device, alone or alongside antibiotics, we can quickly bring blood back to normal conditions, curtailing an inflammatory response rather than exacerbating it,” said Tohid Fatanat Didar, PhD, of the Wyss Institute.

“If all goes well, physicians will someday be able to use the device in tandem with standard antibiotic treatments to deliver a one-two punch to pathogens, synergistically killing and cleansing all live and dead invaders from the bloodstream.”

 

 

As the device has proven effective in small animal experiments, the researchers are planning to move to large animal studies. They must demonstrate proof-of-concept in these models before advancing to clinical trials.

“Our goal is to see this move out of the lab and into hospitals, as well as onto the battlefield,” Dr Ingber said, “where it can save lives within years rather than decades.”

Red blood cells positive

for Staphylococcus infection

Photo by Bill Branson

Last year, researchers reported promising preclinical results with a device that can treat sepsis by mimicking the human spleen. The device filtered pathogens and toxins from the blood by passing it through a dialysis-like circuit.

Now, the researchers have developed a new, more streamlined device that, they believe, is more likely to translate to the clinic. The new device also synergizes with conventional antibiotic therapies.

The team described this device in Biomaterials.

“The inflammatory cascade that leads to sepsis is triggered by pathogens and, specifically, by the toxins they release,” said study author Donald Ingber, MD, PhD, of the Wyss Institute for Biologically Inspired Engineering at Harvard University in Cambridge, Massachusetts.

“Thus, the most effective strategy is to treat with the best antibiotics you can muster, while also removing the toxins and remaining pathogens from the patient’s blood as quickly as possible.”

How the device works

The researchers say their new blood-cleansing approach can be completed quickly, without even identifying the infectious agent. This is because the device uses a proprietary pathogen-capturing agent, known as FcMBL, that binds all types of live and dead infectious microbes, including bacteria, fungi, viruses, and the toxins they release.

FcMBL is a genetically engineered blood protein inspired by a naturally occurring human molecule called mannose binding lectin (MBL). MBL is found in the innate immune system and binds to toxic invaders, marking them for capture by immune cells in the spleen.

The researchers’ original device concept was similar to how a dialysis machine works. Infected blood in an animal, or potentially one day in a patient, is flowed from one vein through catheters to the device.

There, FcMBL-coated magnetic beads are added to the blood, and the bead-bound pathogens are extracted from the circulating blood by magnets within the device before the cleansed blood is returned to the body through another vein.

The new device removes the complexity, regulatory challenges, and cost associated with the magnetic beads and microfluidic architecture of its predecessor. But it still uses the FcMBL protein to bind to pathogens and toxins.

The new system uses hollow fiber filters similar to those currently used in hemodialysis, but the inner walls of these filters are coated with FcMBL protein to remove pathogens from circulating blood.

Test results

In in vitro tests with human blood, the device reduced the number of Gram-negative bacteria (Escherichia coli), Gram-positive bacteria (Staphylococcus aureus), fungi (Candida albicans), and lipopolysaccharide-endotoxins by 90% to 99%.

In tests with rats, the device reduced levels of circulating pathogens and endotoxins by more than 99%, and it prevented pathogen engraftment and inflammatory cell recruitment in the spleen, lung, liver, and kidney.

The researchers also tested the device in combination with bacteriocidal antibiotics in rats. The antibiotics prompted a “major increase” in the release of microbial fragments, or pathogen-associated molecular patterns (PAMPs).

The device could remove PAMPs from the blood within 2 hours, but high levels of PAMPs remained in rats treated with antibiotics alone.

The researchers said PAMP removal reduced organ pathogen and endotoxin loads, suppressed inflammatory responses, and resulted in more stable vital signs.

“Using the device, alone or alongside antibiotics, we can quickly bring blood back to normal conditions, curtailing an inflammatory response rather than exacerbating it,” said Tohid Fatanat Didar, PhD, of the Wyss Institute.

“If all goes well, physicians will someday be able to use the device in tandem with standard antibiotic treatments to deliver a one-two punch to pathogens, synergistically killing and cleansing all live and dead invaders from the bloodstream.”

 

 

As the device has proven effective in small animal experiments, the researchers are planning to move to large animal studies. They must demonstrate proof-of-concept in these models before advancing to clinical trials.

“Our goal is to see this move out of the lab and into hospitals, as well as onto the battlefield,” Dr Ingber said, “where it can save lives within years rather than decades.”

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T-cell finding may have broad implications

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T-cell finding may have broad implications

T cells under a super-

resolution microscope

Image courtesy of UNSW

Early exposure to inflammatory cytokines can “paralyze” CD4 T cells, according to research published in Immunity.

The study suggests this mechanism may act as a firewall, shutting down the immune response before it gets out of hand.

According to researchers, this discovery could lead to more effective immunotherapies for cancer and reduce the need for immunosuppressants in transplant patients, among other applications.

“There’s a 3-signal process to activate T cells, of which each component is essential for proper activation,” said study author Gail Sckisel, PhD, of the University of California, Davis in Sacramento.

“But no one had really looked at what happens if they are delivered out of sequence. If the third signal—cytokines—is given prematurely, it basically paralyzes CD4 T cells.”

To be activated, T cells must first recognize an antigen, receive appropriate costimulatory signals, and then encounter inflammatory cytokines to expand the immune response. Until now, no one realized that sending the third signal early—as is done with some immunotherapies—could actually hamper overall immunity.

“These stimulatory immunotherapies are designed to activate the immune system,” Dr Sckisel explained. “But considering how T cells respond, that approach could damage a patient’s ability to fight off pathogens. While immunotherapies might fight cancer, they may also open the door to opportunistic infections.”

She and her colleagues demonstrated this principle in mice. After they received systemic immunotherapy, the animals had trouble mounting a primary T-cell response.

The researchers confirmed this finding in samples from patients receiving high-dose interleukin 2 to treat metastatic melanoma.

“We need to be very careful because immunotherapy could be generating both short-term gain and long-term loss,” said study author William Murphy, PhD, also of the University of California, Davis.

“The patients who were receiving immunotherapy were totally shut down, which shows how profoundly we were suppressing the immune system.”

In addition to illuminating how T cells respond to cancer immunotherapy, the study also provides insights into autoimmune disorders. The researchers believe this CD4 paralysis mechanism could play a role in preventing autoimmunity, a hypothesis they supported by testing immunotherapy in a multiple sclerosis model.

By shutting down CD4 T cells, immune stimulation prevented an autoimmune response. This provides the opportunity to paralyze the immune system to prevent autoimmunity or modulate it to accept transplanted cells or entire organs.

“Transplant patients go on immunosuppressants for the rest of their lives, but if we could safely induce paralysis just prior to surgery, it’s possible that patients could develop tolerance,” Dr Sckisel said.

CD4 paralysis may also be co-opted by pathogens, such as HIV, which could use this chronic inflammation response to disable the immune system.

“This really highlights the importance of CD4 T cells,” Dr Murphy said. “The fact that they’re regulated and suppressed means they are definitely the orchestrators we need to take into account. It also shows how smart HIV is. The virus has been telling us CD4 T cells are critical because that’s what it attacks.”

The team’s next step is to continue this research in older mice. Age can bring a measurable loss in immune function, and inflammation may play a role in that process.

“For elderly people who have flu or pneumonia, their immune systems are activated, but maybe they can’t fight anything else,” Dr Murphy said. “This could change how we treat people who are very sick. If we can block pathways that suppress the immune response, we may be able to better fight infection.”

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T cells under a super-

resolution microscope

Image courtesy of UNSW

Early exposure to inflammatory cytokines can “paralyze” CD4 T cells, according to research published in Immunity.

The study suggests this mechanism may act as a firewall, shutting down the immune response before it gets out of hand.

According to researchers, this discovery could lead to more effective immunotherapies for cancer and reduce the need for immunosuppressants in transplant patients, among other applications.

“There’s a 3-signal process to activate T cells, of which each component is essential for proper activation,” said study author Gail Sckisel, PhD, of the University of California, Davis in Sacramento.

“But no one had really looked at what happens if they are delivered out of sequence. If the third signal—cytokines—is given prematurely, it basically paralyzes CD4 T cells.”

To be activated, T cells must first recognize an antigen, receive appropriate costimulatory signals, and then encounter inflammatory cytokines to expand the immune response. Until now, no one realized that sending the third signal early—as is done with some immunotherapies—could actually hamper overall immunity.

“These stimulatory immunotherapies are designed to activate the immune system,” Dr Sckisel explained. “But considering how T cells respond, that approach could damage a patient’s ability to fight off pathogens. While immunotherapies might fight cancer, they may also open the door to opportunistic infections.”

She and her colleagues demonstrated this principle in mice. After they received systemic immunotherapy, the animals had trouble mounting a primary T-cell response.

The researchers confirmed this finding in samples from patients receiving high-dose interleukin 2 to treat metastatic melanoma.

“We need to be very careful because immunotherapy could be generating both short-term gain and long-term loss,” said study author William Murphy, PhD, also of the University of California, Davis.

“The patients who were receiving immunotherapy were totally shut down, which shows how profoundly we were suppressing the immune system.”

In addition to illuminating how T cells respond to cancer immunotherapy, the study also provides insights into autoimmune disorders. The researchers believe this CD4 paralysis mechanism could play a role in preventing autoimmunity, a hypothesis they supported by testing immunotherapy in a multiple sclerosis model.

By shutting down CD4 T cells, immune stimulation prevented an autoimmune response. This provides the opportunity to paralyze the immune system to prevent autoimmunity or modulate it to accept transplanted cells or entire organs.

“Transplant patients go on immunosuppressants for the rest of their lives, but if we could safely induce paralysis just prior to surgery, it’s possible that patients could develop tolerance,” Dr Sckisel said.

CD4 paralysis may also be co-opted by pathogens, such as HIV, which could use this chronic inflammation response to disable the immune system.

“This really highlights the importance of CD4 T cells,” Dr Murphy said. “The fact that they’re regulated and suppressed means they are definitely the orchestrators we need to take into account. It also shows how smart HIV is. The virus has been telling us CD4 T cells are critical because that’s what it attacks.”

The team’s next step is to continue this research in older mice. Age can bring a measurable loss in immune function, and inflammation may play a role in that process.

“For elderly people who have flu or pneumonia, their immune systems are activated, but maybe they can’t fight anything else,” Dr Murphy said. “This could change how we treat people who are very sick. If we can block pathways that suppress the immune response, we may be able to better fight infection.”

T cells under a super-

resolution microscope

Image courtesy of UNSW

Early exposure to inflammatory cytokines can “paralyze” CD4 T cells, according to research published in Immunity.

The study suggests this mechanism may act as a firewall, shutting down the immune response before it gets out of hand.

According to researchers, this discovery could lead to more effective immunotherapies for cancer and reduce the need for immunosuppressants in transplant patients, among other applications.

“There’s a 3-signal process to activate T cells, of which each component is essential for proper activation,” said study author Gail Sckisel, PhD, of the University of California, Davis in Sacramento.

“But no one had really looked at what happens if they are delivered out of sequence. If the third signal—cytokines—is given prematurely, it basically paralyzes CD4 T cells.”

To be activated, T cells must first recognize an antigen, receive appropriate costimulatory signals, and then encounter inflammatory cytokines to expand the immune response. Until now, no one realized that sending the third signal early—as is done with some immunotherapies—could actually hamper overall immunity.

“These stimulatory immunotherapies are designed to activate the immune system,” Dr Sckisel explained. “But considering how T cells respond, that approach could damage a patient’s ability to fight off pathogens. While immunotherapies might fight cancer, they may also open the door to opportunistic infections.”

She and her colleagues demonstrated this principle in mice. After they received systemic immunotherapy, the animals had trouble mounting a primary T-cell response.

The researchers confirmed this finding in samples from patients receiving high-dose interleukin 2 to treat metastatic melanoma.

“We need to be very careful because immunotherapy could be generating both short-term gain and long-term loss,” said study author William Murphy, PhD, also of the University of California, Davis.

“The patients who were receiving immunotherapy were totally shut down, which shows how profoundly we were suppressing the immune system.”

In addition to illuminating how T cells respond to cancer immunotherapy, the study also provides insights into autoimmune disorders. The researchers believe this CD4 paralysis mechanism could play a role in preventing autoimmunity, a hypothesis they supported by testing immunotherapy in a multiple sclerosis model.

By shutting down CD4 T cells, immune stimulation prevented an autoimmune response. This provides the opportunity to paralyze the immune system to prevent autoimmunity or modulate it to accept transplanted cells or entire organs.

“Transplant patients go on immunosuppressants for the rest of their lives, but if we could safely induce paralysis just prior to surgery, it’s possible that patients could develop tolerance,” Dr Sckisel said.

CD4 paralysis may also be co-opted by pathogens, such as HIV, which could use this chronic inflammation response to disable the immune system.

“This really highlights the importance of CD4 T cells,” Dr Murphy said. “The fact that they’re regulated and suppressed means they are definitely the orchestrators we need to take into account. It also shows how smart HIV is. The virus has been telling us CD4 T cells are critical because that’s what it attacks.”

The team’s next step is to continue this research in older mice. Age can bring a measurable loss in immune function, and inflammation may play a role in that process.

“For elderly people who have flu or pneumonia, their immune systems are activated, but maybe they can’t fight anything else,” Dr Murphy said. “This could change how we treat people who are very sick. If we can block pathways that suppress the immune response, we may be able to better fight infection.”

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NICE drafts guideline for treating myeloma patients

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Doctor and patient

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The National Institute for Health and Care Excellence (NICE) has developed a draft guideline detailing “best practices” in caring for patients with myeloma.

It is intended to help ensure “consistently excellent care” for myeloma patients over the age of 16 in England.

The guideline includes recommendations for diagnosing the disease, managing complications, communicating with patients, and ensuring access to appropriate care.

The draft guideline will remain open for public consultation until October 1, 2015.

“Advances in treatment over the last 15 years have seen more people with myeloma living longer, but there is still no cure,” said Mark Baker, clinical practice director for NICE.

“Our guideline, which is being developed by an independent group of experts, will set out best-practice care to ensure people live as normal a life as possible for as long as possible.”

The guideline’s provisional recommendations are as follows.

Communication and support: Offer prompt psychological assessment and support to myeloma patients at diagnosis and, as appropriate, at the beginning and end of each treatment, when the disease progresses, and when patients start to require end-of-life care.

Laboratory investigations to diagnose myeloma: For patients with suspected myeloma, healthcare professionals should use the same sample for all diagnostic and prognostic tests on bone marrow, so patients only have to have one biopsy.

Scans for patients with suspected myeloma: Offer imaging to all patients with a plasma cell disorder suspected to be myeloma. Doctors should consider whole-body MRI as the first imaging procedure.

Service delivery: Each hospital treating patients with myeloma who are over the age of 18 should ensure there is regional access to facilities for intensive inpatient chemotherapy or transplantation, renal support, spinal disease management, specialized pain management, therapeutic apheresis, radiotherapy, restorative dentistry and oral surgery, and clinical trials, particularly early phase trials.

Managing complications: Healthcare professionals should consider extending the pneumococcal vaccination to patients with myeloma who are under 65 in order to prevent infection.

This draft guideline also complements existing NICE guidance on the drug treatment of myeloma. It sets out which treatments—including stem cell transplants—should be used to manage the condition as well as those to prevent and treat bone disease and acute renal disease, which can be caused by myeloma.

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Doctor and patient

Photo courtesy of NIH

The National Institute for Health and Care Excellence (NICE) has developed a draft guideline detailing “best practices” in caring for patients with myeloma.

It is intended to help ensure “consistently excellent care” for myeloma patients over the age of 16 in England.

The guideline includes recommendations for diagnosing the disease, managing complications, communicating with patients, and ensuring access to appropriate care.

The draft guideline will remain open for public consultation until October 1, 2015.

“Advances in treatment over the last 15 years have seen more people with myeloma living longer, but there is still no cure,” said Mark Baker, clinical practice director for NICE.

“Our guideline, which is being developed by an independent group of experts, will set out best-practice care to ensure people live as normal a life as possible for as long as possible.”

The guideline’s provisional recommendations are as follows.

Communication and support: Offer prompt psychological assessment and support to myeloma patients at diagnosis and, as appropriate, at the beginning and end of each treatment, when the disease progresses, and when patients start to require end-of-life care.

Laboratory investigations to diagnose myeloma: For patients with suspected myeloma, healthcare professionals should use the same sample for all diagnostic and prognostic tests on bone marrow, so patients only have to have one biopsy.

Scans for patients with suspected myeloma: Offer imaging to all patients with a plasma cell disorder suspected to be myeloma. Doctors should consider whole-body MRI as the first imaging procedure.

Service delivery: Each hospital treating patients with myeloma who are over the age of 18 should ensure there is regional access to facilities for intensive inpatient chemotherapy or transplantation, renal support, spinal disease management, specialized pain management, therapeutic apheresis, radiotherapy, restorative dentistry and oral surgery, and clinical trials, particularly early phase trials.

Managing complications: Healthcare professionals should consider extending the pneumococcal vaccination to patients with myeloma who are under 65 in order to prevent infection.

This draft guideline also complements existing NICE guidance on the drug treatment of myeloma. It sets out which treatments—including stem cell transplants—should be used to manage the condition as well as those to prevent and treat bone disease and acute renal disease, which can be caused by myeloma.

Doctor and patient

Photo courtesy of NIH

The National Institute for Health and Care Excellence (NICE) has developed a draft guideline detailing “best practices” in caring for patients with myeloma.

It is intended to help ensure “consistently excellent care” for myeloma patients over the age of 16 in England.

The guideline includes recommendations for diagnosing the disease, managing complications, communicating with patients, and ensuring access to appropriate care.

The draft guideline will remain open for public consultation until October 1, 2015.

“Advances in treatment over the last 15 years have seen more people with myeloma living longer, but there is still no cure,” said Mark Baker, clinical practice director for NICE.

“Our guideline, which is being developed by an independent group of experts, will set out best-practice care to ensure people live as normal a life as possible for as long as possible.”

The guideline’s provisional recommendations are as follows.

Communication and support: Offer prompt psychological assessment and support to myeloma patients at diagnosis and, as appropriate, at the beginning and end of each treatment, when the disease progresses, and when patients start to require end-of-life care.

Laboratory investigations to diagnose myeloma: For patients with suspected myeloma, healthcare professionals should use the same sample for all diagnostic and prognostic tests on bone marrow, so patients only have to have one biopsy.

Scans for patients with suspected myeloma: Offer imaging to all patients with a plasma cell disorder suspected to be myeloma. Doctors should consider whole-body MRI as the first imaging procedure.

Service delivery: Each hospital treating patients with myeloma who are over the age of 18 should ensure there is regional access to facilities for intensive inpatient chemotherapy or transplantation, renal support, spinal disease management, specialized pain management, therapeutic apheresis, radiotherapy, restorative dentistry and oral surgery, and clinical trials, particularly early phase trials.

Managing complications: Healthcare professionals should consider extending the pneumococcal vaccination to patients with myeloma who are under 65 in order to prevent infection.

This draft guideline also complements existing NICE guidance on the drug treatment of myeloma. It sets out which treatments—including stem cell transplants—should be used to manage the condition as well as those to prevent and treat bone disease and acute renal disease, which can be caused by myeloma.

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Primary Medication Nonadherence

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Refractory primary medication nonadherence: Prevalence and predictors after pharmacist counseling at hospital discharge

Medication nonadherence after hospital discharge impacts morbidity and mortality in patients with cardiovascular disease.[1] Primary nonadherence, part of the spectrum of medication underuse, occurs when a patient receives a prescription but does not fill it.[1] Prior studies utilizing retrospective administrative data have found a prevalence of postdischarge primary nonadherence between 24% and 28%,[1, 2] similar to findings in a variety of outpatient populations.[3, 4]

One strategy for reduction in nonadherence is discharge medication counseling, which has been associated with improved postdischarge outcomes.[1] We evaluated the prevalence and predictors of refractory primary nonadherence in a cohort of patients hospitalized for acute cardiovascular conditions who received pharmacist counseling prior to discharge to guide future adherence interventions.

METHODS

Setting and Participants

The present study represents a secondary analysis of data from the Pharmacist Intervention for Low Literacy in Cardiovascular Disease (PILL‐CVD) study. PILL‐CVD was a randomized controlled trial that evaluated the effect of a tailored intervention consisting of pharmacist‐assisted medication reconciliation, discharge counseling, low‐literacy adherence aids, and follow‐up phone calls in adults hospitalized for acute coronary syndromes or acute decompensated heart failure. Patients likely to be discharged home taking primary responsibility for their medication management were eligible. Full study methods and results, including inclusion and exclusion criteria, can be found elsewhere.[5] The institutional review boards of each site approved the study.

For the present analysis, patients were included if they had any new discharge prescriptions to fill and received the study intervention, including a postdischarge follow‐up phone call with questions about filling discharge prescriptions.

Baseline Measures

Baseline data were obtained from medical records and patient interviews, including demographic information as well as survey data for cognitive impairment (Mini‐Cog) and health literacy (Short Test of Functional Health Literacy in Adults).[6, 7]

Data were also collected related to medication use, including the number of scheduled and as‐needed medications listed at discharge, self‐reported preadmission adherence, medication understanding, and medication management practices (eg, use of a pillbox, refill reminders). Self‐reported medication adherence was measured with the 4‐item Morisky scale.[8] Medication understanding was assessed with a tool previously developed by Marvanova et al.[9]

Outcome Measures

The primary outcome was the percentage of patients who reported not filling at least 1 discharge prescription on a telephone call that was conducted 1 to 4 days postdischarge. Patients were asked a dichotomous question about whether or not they filled all of their discharge prescriptions. Further characterization of the class or number of medications not filled was not performed. Patients were asked to provide a reason for not filling the prescriptions.

Analysis

We evaluated the prevalence and possible predictors of primary nonadherence including age, gender, race, marital status, education and income levels, insurance type, health literacy, cognition, presence of a primary care physician, number of listed discharge medications, prehospital medication adherence, medication understanding, and medication management practices using Pearson 2, Fisher exact, or Wilcoxon rank sum tests as appropriate. Multiple logistic regression with backward elimination was performed to identify independent predictors, selected with P values<0.1. We also evaluated reasons that patients cited for not filling prescriptions. Two‐sided P values<0.05 were considered statistically significant. All analyses were conducted using Stata version 13.1 (StataCorp LP, College Station, TX).

RESULTS

Of 851 patients in the PILL‐CVD study, the present sample includes 341 patients who received the intervention, completed the postdischarge follow‐up call, and had new discharge prescriptions to be filled. This represents 85% of patients who received the intervention.

The mean age of participants was 61.3 years, and 59.5% were male (Table 1). The majority were white (75.1%), and 88% had at least a high school education. Married or cohabitating patients represented 54.3% of the group. Just over half of the patients (54%) had an income of $35K or greater. The primary source of insurance for 82.5% of patients was either Medicare or private insurance, and 7.4% of patients were self‐pay. Most patients (80%) had adequate health literacy. The median Mini‐Cog score was 4 out of 5 (interquartile range [IQR]=35), and 11% of patients had scores indicating cognitive impairment. Just less than one‐fourth of the patients (24.1%) had a Morisky score of 8, indicating high self‐reported adherence, and the median score of patients' understanding of medications (range of 03) was 2.5 (IQR=2.22.8), reflecting relatively high understanding. The median number of prescriptions on patients' discharge medications lists was 10 (IQR=813).

Patient Characteristics
Variable Overall 341 (100.0%) Filled Prescription309 (90.6%) Did Not Fill 32 (9.4%) P Value
  • NOTE: Missing values are present in the following categories: race (n=3), income (n=28), insurance (n=5).

  • Pearson 2 test.

  • P<0.05.

  • Fisher exact test (2‐sided).

Age, y, N (%) 0.745a
1849 69 63 (91.3) 6 (8.7)
5064 128 114 (89.1) 14 (10.9)
65+ 144 132 (91.7) 12 (8.3)
Gender, N (%) 0.056a
Male 203 189 (93.1) 14 (6.9)
Female 138 120 (87.0) 18 (13.0)
Race, N (%) 0.712a
White 256 234 (91.4) 22 (8.6)
African American 60 54 (90.0) 6 (10.0)
Other 22 19 (86.4) 3 (13.6)
Education, N (%) 0.054a
Less than high school 40 32 (80.0) 8 (20.0)
High school 99 91 (91.9) 8 (8.1)
1315 years 93 83 (89.2) 10 (10.8)
16 years 109 103 (94.5) 6 (5.5)
Marital status, N (%)
Separated/divorced/widowed/never married 156 135 (86.5) 21 (13.5) 0.018a, b
Married/cohabitating 185 174 (94.1) 11 (5.9)
Income, N (%) 0.040a, b
<10K<20K 58 48 (82.8) 10 (17.2)
20K35K 86 76 (88.4) 10 (11.6)
35K<50K 40 36 (90.0) 4 (10.0)
50K<75K 46 43 (93.5) 3 (6.5)
75K+ 83 81 (97.6) 2 (2.4)
Primary source of payment, N (%) 0.272a
Medicaid 34 28 (82.4) 6 (17.6)
Medicare 145 131 (90.3) 14 (9.7)
Private 132 123 (93.2) 9 (6.8)
Self‐pay 25 22 (88.0) 3 (12.0)
Primary care physician, N (%) 1.000c
None/do not know 28 26 (92.9) 2 (7.1)
Yes 313 283 (90.4) 30 (9.6)
Site, N (%) 0.071a
Nashville, TN 172 151 (87.8) 21 (12.2)
Boston, MA 169 158 (93.5) 11 (6.5)

The prevalence of refractory primary nonadherence was 9.4%. In univariate analysis, single marital status, lower income, and having more than 10 total discharge medications were significantly associated with not filling medications (P=0.018, 0.04, 0.016, respectively; Table 1). In multivariable analysis, single marital status and having more than 10 total discharge medications maintained significance when controlling for other patient characteristics. Patients who were single had higher odds of failing to fill discharge prescriptions compared to married or cohabitating individuals (odds ratio [OR]: 2.2, 95% confidence interval [CI]: 1.014.8, P=0.047). Patients with more than 10 discharge medications also had higher odds of failing to fill compared with patients who had fewer total medications (OR: 2.3, 95% CI: 1.054.98, P=0.036).

Filling discharge prescriptions was not associated with health literacy, cognition, prehospital adherence, patients' medication understanding, or any of the surveyed medication management practices (Table 2). Patients' reasons for not filling included lack of time to go to the pharmacy, medications not being delivered or dispensed, or inability to afford prescriptions. Prescription cost was cited by 23.5% of patients who did not fill their prescriptions and provided a reason.

Patient Medication‐Related Characteristics
Variable Overall 341 (100.0%) Filled Prescription 309 (90.6%) Did Not Fill 32 (9.4%) P Value
  • NOTE: Missing values are present in the following categories: s‐TOFHLA (n=6), Morisky (n=13). Abbreviations: s‐TOFHLA, Short Test of Functional Health Literacy in Adults.

  • Pearson 2 test.

  • Fisher exact test (2‐sided).

  • Number on discharge medication list.

s‐TOFHLA score, range 036, N (%) 0.443a
Inadequate, 016 40 34 (85.0) 6 (15.0)
Marginal, 1722 27 25 (92.6) 2 (7.4)
Adequate, 2336 268 244 (91.0) 24 (9.0)
MiniCog score, range 05, N (%) 0.764b
Not impaired, 35 304 276 (90.8) 28 (9.2)
Impaired, 02 37 33 (89.2) 4 (10.8)
Morisky score, range 48, N (%) 0.517a
Low/moderate self‐reported adherence, 47 249 224 (90.0) 25 (10.0)
High self‐reported adherence, 8 79 73 (92.4) 6 (7.6)
No. of discharge medications, range 126, N (%)c 0.016a
010 medications 186 175 (94.1) 11 (5.9)
11+medications 155 134 (86.5) 21 (13.5)
Patient responses to medication behavior questions
Patient associates medication taking time with daily events 253 229 (90.5) 24 (9.5) 0.913a
Patient uses a pillbox to organize medicine 180 162 (90.0) 18 (10.0) 0.680a
Friends of family help remind patient when it is time to take medicine 89 79 (88.8) 10 (11.2) 0.486a
Patient writes down instructions for when to take medicine 60 55 (91.7) 5 (8.3) 0.758a
Patient uses an alarm or a reminder that beeps when it is time to take medicine 8 6 (75.0) 2 (25.0) 0.167a
Patient marks refill date on calendar 38 35 (92.1) 3 (7.9) 1.000b
Pharmacy gives or sends patient a reminder when it is time to refill medicine 94 84 (89.4) 10 (10.6) 0.624a
Friends or family help patient to refill medicine 60 53 (88.3) 7 (11.7) 0.504a

DISCUSSION

Almost 1 in 10 patients hospitalized with cardiovascular disease demonstrated primary nonadherence refractory to an intervention including pharmacist discharge medication counseling. Being unmarried and having greater than 10 medications at discharge were significantly associated with higher primary nonadherence when controlling for other patient factors.

Patients with a cohabitant partner were significantly less likely to exhibit primary nonadherence, which may reflect higher levels of social support, including encouragement for disease self‐management and/or support with tasks such as picking up medications from the pharmacy. Previous research has demonstrated that social support mediates outpatient medication adherence for heart failure patients.[10]

Similar to Jackevicius et al., we found that patients with more medications at discharge were less likely to fill their prescriptions.[1] These findings may reflect the challenges that patients face in adhering to complex treatment plans, which are associated with increased coordination and cost. Conversely, some prior studies have found that patients with fewer prescriptions were less likely to fill.[11, 12] These patients were often younger, thus potentially less conditioned to fill prescriptions, and unlike our cohort, these populations had consistent prescription coverage. Interventions for polypharmacy, which have been shown to improve outcomes and decrease costs, especially in the geriatric population, may be of benefit for primary nonadherence as well.[13]

Additionally, patients with lower household incomes had higher rates of primary nonadherence, at least in univariate analysis. Medication cost and transportation limitations, which are more pronounced in lower‐income patients, likely play influential roles in this group. These findings build on prior literature that has found lower prescription cost to be associated with better medication adherence in a variety of settings.[3, 4, 14]

Because the prevalence of primary nonadherence in this cohort is less than half of historical rates, we suspect the intervention did reduce unintentional nonadherence. However, regimen cost and complexity, transportation challenges, and ingrained medication beliefs likely remained barriers. It may be that a postdischarge phone call is able address unintended primary nonadherence in many cases. Meds to beds programs, where a supply of medications is provided to patients prior to discharge, could assist patients with limited transportation. Prior studies have also found reduced primary nonadherence when e‐prescriptions are utilized.[3]

Establishing outpatient follow‐up at discharge provides additional opportunities to address unanticipated adherence barriers. Because the efficacy of any adherence intervention depends on individual patient barriers, we recommend combining medication counseling with a targeted approach for patient‐specific needs.

We note several limitations to our study. First, because we studied primary nonadherence that persisted despite an intervention, this cohort likely underestimates the prevalence of primary nonadherence and alters the associated patient characteristics found in routine practice (although counseling is becoming more common). Second, patient reporting is subject to biases that underestimate nonadherence, although this approach has been validated previously.[15] Third, our outcome measure was unable to capture the spectrum of non‐adherence that could provide a more nuanced look at predictors of postdischarge nonadherence. Fourth, we did not have patient copayment data to better characterize whether out of pocket costs or pharmacologic classes drove nonadherence. Finally, sample size may have limited the detection of other important factors, and the university setting may limit generalizability to cardiovascular patients in other practice environments. Future research should focus on intervention strategies that assess patients' individual adherence barriers for a targeted or multimodal approach to improve adherence.

In conclusion, we found a prevalence of primary nonadherence of almost 1 in 10 patients who received pharmacist counseling. Nonadherence was associated with being single and those discharged with longer medication lists. Our results support existing literature that primary nonadherence is a significant problem in the postdischarge setting and substantiate the need for ongoing efforts to study and implement interventions for adherence after hospital discharge.

Disclosures

This material is based on work supported by the Office of Academic Affiliations, Department of Veterans Affairs, Veterans Affairs National Quality Scholars Program, and with use of facilities at Veterans Affairs Tennessee Valley Healthcare System, Nashville, Tennessee (Dr. Wooldridge). The funding agency supported the work indirectly through provision of salary support and training for the primary author, but had no specific role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; or decision to submit the manuscript for publication. This work was also supported by R01 HL089755 (Dr. Kripalani) and in part by K23 HL077597 (Dr. Kripalani), K08 HL072806 (Dr. Schnipper), and the Center for Clinical Quality and Implementation Research at Vanderbilt University Medical Center. A preliminary version of this research was presented at the AcademyHealth Annual Research Meeting, June 16, 2015, Minneapolis, Minnesota. The authors report the following potential conflicts of interest: Jeffrey Schnipper: PI, investigator‐initiated study funded by Sanofi‐Aventis to develop, implement, and evaluate a multifaceted intervention to improve transitions of care in patients with diabetes mellitus discharged on insulin. Robert Dittus: passive co‐owner, Medical Decision Modeling, Inc.; Bayer HealthCare. One‐day consultation and panelist on educational video for population health (consultant fee); GlaxoSmithKline. One‐day consultant for population health, envisioning the future (consultant fee). Sunil Kripalani: Bioscape Digital, stock ownership

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References
  1. Jackevicius CA, Li P, Tu JV. Prevalence, predictors, and outcomes of primary nonadherence after acute myocardial infarction. Circulation. 2008;117(8):10281036.
  2. Fallis BA, Dhalla IA, Klemensberg J, Bell CM. Primary medication non‐adherence after discharge from a general internal medicine service. PloS One. 2013;8(5):e61735.
  3. Fischer MA, Choudhry NK, Brill G, et al. Trouble getting started: predictors of primary medication nonadherence. Am J Med. 2011;124(11):1081.e9–22.
  4. Tamblyn R, Eguale T, Huang A, Winslade N, Doran P. The incidence and determinants of primary nonadherence with prescribed medication in primary care: a cohort study. Ann Intern Med. 2014;160(7):441450.
  5. Kripalani S, Roumie CL, Dalal AK, et al. Effect of a pharmacist intervention on clinically important medication errors after hospital discharge: a randomized trial. Ann Intern Med. 2012;157(1):110.
  6. Nurss J, Parker R, Williams M, Baker D. Short Test of Functional Health Literacy in Adults. Snow Camp, NC: Peppercorn Books and Press; 1998.
  7. Borson S, Scanlan JM, Watanabe J, Tu SP, Lessig M. Simplifying detection of cognitive impairment: comparison of the Mini‐Cog and Mini‐Mental State Examination in a multiethnic sample. J Am Geriatr Soc. 2005;53(5):871874.
  8. Morisky DE, Green LW, Levine DM. Concurrent and predictive validity of a self‐reported measure of medication adherence. Med Care. 1986;24(1):6774.
  9. Marvanova M, Roumie CL, Eden SK, Cawthon C, Schnipper JL, Kripalani S. Health literacy and medication understanding among hospitalized adults. J Hosp Med. 2011;6(9):488493.
  10. Wu JR, Frazier SK, Rayens MK, Lennie TA, Chung ML, Moser DK. Medication adherence, social support, and event‐free survival in patients with heart failure. Health Psychol. 2013;32(6):637646.
  11. Lagu T, Weiner MG, Eachus S, Tang SS, Schwartz JS, Turner BJ. Effect of patient comorbidities on filling of antihypertensive prescriptions. Am J Manag Care. 2009;15(1):2430.
  12. Cheetham TC, Niu F, Green K, et al. Primary nonadherence to statin medications in a managed care organization. J Manag Care Pharm. 2013;19(5):367373.
  13. Kojima G, Bell C, Tamura B, et al. Reducing cost by reducing polypharmacy: the polypharmacy outcomes project. J Am Med Dir Assoc. 2012;13(9):818.e811–815.
  14. Shrank WH, Choudhry NK, Fischer MA, et al. The epidemiology of prescriptions abandoned at the pharmacy. Ann Intern Med. 2010;153(10):633640.
  15. Haynes RB, Taylor DW, Sackett DL, Gibson ES, Bernholz CD, Mukherjee J. Can simple clinical measurements detect patient noncompliance? Hypertension. 1980;2(6):757764.
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Medication nonadherence after hospital discharge impacts morbidity and mortality in patients with cardiovascular disease.[1] Primary nonadherence, part of the spectrum of medication underuse, occurs when a patient receives a prescription but does not fill it.[1] Prior studies utilizing retrospective administrative data have found a prevalence of postdischarge primary nonadherence between 24% and 28%,[1, 2] similar to findings in a variety of outpatient populations.[3, 4]

One strategy for reduction in nonadherence is discharge medication counseling, which has been associated with improved postdischarge outcomes.[1] We evaluated the prevalence and predictors of refractory primary nonadherence in a cohort of patients hospitalized for acute cardiovascular conditions who received pharmacist counseling prior to discharge to guide future adherence interventions.

METHODS

Setting and Participants

The present study represents a secondary analysis of data from the Pharmacist Intervention for Low Literacy in Cardiovascular Disease (PILL‐CVD) study. PILL‐CVD was a randomized controlled trial that evaluated the effect of a tailored intervention consisting of pharmacist‐assisted medication reconciliation, discharge counseling, low‐literacy adherence aids, and follow‐up phone calls in adults hospitalized for acute coronary syndromes or acute decompensated heart failure. Patients likely to be discharged home taking primary responsibility for their medication management were eligible. Full study methods and results, including inclusion and exclusion criteria, can be found elsewhere.[5] The institutional review boards of each site approved the study.

For the present analysis, patients were included if they had any new discharge prescriptions to fill and received the study intervention, including a postdischarge follow‐up phone call with questions about filling discharge prescriptions.

Baseline Measures

Baseline data were obtained from medical records and patient interviews, including demographic information as well as survey data for cognitive impairment (Mini‐Cog) and health literacy (Short Test of Functional Health Literacy in Adults).[6, 7]

Data were also collected related to medication use, including the number of scheduled and as‐needed medications listed at discharge, self‐reported preadmission adherence, medication understanding, and medication management practices (eg, use of a pillbox, refill reminders). Self‐reported medication adherence was measured with the 4‐item Morisky scale.[8] Medication understanding was assessed with a tool previously developed by Marvanova et al.[9]

Outcome Measures

The primary outcome was the percentage of patients who reported not filling at least 1 discharge prescription on a telephone call that was conducted 1 to 4 days postdischarge. Patients were asked a dichotomous question about whether or not they filled all of their discharge prescriptions. Further characterization of the class or number of medications not filled was not performed. Patients were asked to provide a reason for not filling the prescriptions.

Analysis

We evaluated the prevalence and possible predictors of primary nonadherence including age, gender, race, marital status, education and income levels, insurance type, health literacy, cognition, presence of a primary care physician, number of listed discharge medications, prehospital medication adherence, medication understanding, and medication management practices using Pearson 2, Fisher exact, or Wilcoxon rank sum tests as appropriate. Multiple logistic regression with backward elimination was performed to identify independent predictors, selected with P values<0.1. We also evaluated reasons that patients cited for not filling prescriptions. Two‐sided P values<0.05 were considered statistically significant. All analyses were conducted using Stata version 13.1 (StataCorp LP, College Station, TX).

RESULTS

Of 851 patients in the PILL‐CVD study, the present sample includes 341 patients who received the intervention, completed the postdischarge follow‐up call, and had new discharge prescriptions to be filled. This represents 85% of patients who received the intervention.

The mean age of participants was 61.3 years, and 59.5% were male (Table 1). The majority were white (75.1%), and 88% had at least a high school education. Married or cohabitating patients represented 54.3% of the group. Just over half of the patients (54%) had an income of $35K or greater. The primary source of insurance for 82.5% of patients was either Medicare or private insurance, and 7.4% of patients were self‐pay. Most patients (80%) had adequate health literacy. The median Mini‐Cog score was 4 out of 5 (interquartile range [IQR]=35), and 11% of patients had scores indicating cognitive impairment. Just less than one‐fourth of the patients (24.1%) had a Morisky score of 8, indicating high self‐reported adherence, and the median score of patients' understanding of medications (range of 03) was 2.5 (IQR=2.22.8), reflecting relatively high understanding. The median number of prescriptions on patients' discharge medications lists was 10 (IQR=813).

Patient Characteristics
Variable Overall 341 (100.0%) Filled Prescription309 (90.6%) Did Not Fill 32 (9.4%) P Value
  • NOTE: Missing values are present in the following categories: race (n=3), income (n=28), insurance (n=5).

  • Pearson 2 test.

  • P<0.05.

  • Fisher exact test (2‐sided).

Age, y, N (%) 0.745a
1849 69 63 (91.3) 6 (8.7)
5064 128 114 (89.1) 14 (10.9)
65+ 144 132 (91.7) 12 (8.3)
Gender, N (%) 0.056a
Male 203 189 (93.1) 14 (6.9)
Female 138 120 (87.0) 18 (13.0)
Race, N (%) 0.712a
White 256 234 (91.4) 22 (8.6)
African American 60 54 (90.0) 6 (10.0)
Other 22 19 (86.4) 3 (13.6)
Education, N (%) 0.054a
Less than high school 40 32 (80.0) 8 (20.0)
High school 99 91 (91.9) 8 (8.1)
1315 years 93 83 (89.2) 10 (10.8)
16 years 109 103 (94.5) 6 (5.5)
Marital status, N (%)
Separated/divorced/widowed/never married 156 135 (86.5) 21 (13.5) 0.018a, b
Married/cohabitating 185 174 (94.1) 11 (5.9)
Income, N (%) 0.040a, b
<10K<20K 58 48 (82.8) 10 (17.2)
20K35K 86 76 (88.4) 10 (11.6)
35K<50K 40 36 (90.0) 4 (10.0)
50K<75K 46 43 (93.5) 3 (6.5)
75K+ 83 81 (97.6) 2 (2.4)
Primary source of payment, N (%) 0.272a
Medicaid 34 28 (82.4) 6 (17.6)
Medicare 145 131 (90.3) 14 (9.7)
Private 132 123 (93.2) 9 (6.8)
Self‐pay 25 22 (88.0) 3 (12.0)
Primary care physician, N (%) 1.000c
None/do not know 28 26 (92.9) 2 (7.1)
Yes 313 283 (90.4) 30 (9.6)
Site, N (%) 0.071a
Nashville, TN 172 151 (87.8) 21 (12.2)
Boston, MA 169 158 (93.5) 11 (6.5)

The prevalence of refractory primary nonadherence was 9.4%. In univariate analysis, single marital status, lower income, and having more than 10 total discharge medications were significantly associated with not filling medications (P=0.018, 0.04, 0.016, respectively; Table 1). In multivariable analysis, single marital status and having more than 10 total discharge medications maintained significance when controlling for other patient characteristics. Patients who were single had higher odds of failing to fill discharge prescriptions compared to married or cohabitating individuals (odds ratio [OR]: 2.2, 95% confidence interval [CI]: 1.014.8, P=0.047). Patients with more than 10 discharge medications also had higher odds of failing to fill compared with patients who had fewer total medications (OR: 2.3, 95% CI: 1.054.98, P=0.036).

Filling discharge prescriptions was not associated with health literacy, cognition, prehospital adherence, patients' medication understanding, or any of the surveyed medication management practices (Table 2). Patients' reasons for not filling included lack of time to go to the pharmacy, medications not being delivered or dispensed, or inability to afford prescriptions. Prescription cost was cited by 23.5% of patients who did not fill their prescriptions and provided a reason.

Patient Medication‐Related Characteristics
Variable Overall 341 (100.0%) Filled Prescription 309 (90.6%) Did Not Fill 32 (9.4%) P Value
  • NOTE: Missing values are present in the following categories: s‐TOFHLA (n=6), Morisky (n=13). Abbreviations: s‐TOFHLA, Short Test of Functional Health Literacy in Adults.

  • Pearson 2 test.

  • Fisher exact test (2‐sided).

  • Number on discharge medication list.

s‐TOFHLA score, range 036, N (%) 0.443a
Inadequate, 016 40 34 (85.0) 6 (15.0)
Marginal, 1722 27 25 (92.6) 2 (7.4)
Adequate, 2336 268 244 (91.0) 24 (9.0)
MiniCog score, range 05, N (%) 0.764b
Not impaired, 35 304 276 (90.8) 28 (9.2)
Impaired, 02 37 33 (89.2) 4 (10.8)
Morisky score, range 48, N (%) 0.517a
Low/moderate self‐reported adherence, 47 249 224 (90.0) 25 (10.0)
High self‐reported adherence, 8 79 73 (92.4) 6 (7.6)
No. of discharge medications, range 126, N (%)c 0.016a
010 medications 186 175 (94.1) 11 (5.9)
11+medications 155 134 (86.5) 21 (13.5)
Patient responses to medication behavior questions
Patient associates medication taking time with daily events 253 229 (90.5) 24 (9.5) 0.913a
Patient uses a pillbox to organize medicine 180 162 (90.0) 18 (10.0) 0.680a
Friends of family help remind patient when it is time to take medicine 89 79 (88.8) 10 (11.2) 0.486a
Patient writes down instructions for when to take medicine 60 55 (91.7) 5 (8.3) 0.758a
Patient uses an alarm or a reminder that beeps when it is time to take medicine 8 6 (75.0) 2 (25.0) 0.167a
Patient marks refill date on calendar 38 35 (92.1) 3 (7.9) 1.000b
Pharmacy gives or sends patient a reminder when it is time to refill medicine 94 84 (89.4) 10 (10.6) 0.624a
Friends or family help patient to refill medicine 60 53 (88.3) 7 (11.7) 0.504a

DISCUSSION

Almost 1 in 10 patients hospitalized with cardiovascular disease demonstrated primary nonadherence refractory to an intervention including pharmacist discharge medication counseling. Being unmarried and having greater than 10 medications at discharge were significantly associated with higher primary nonadherence when controlling for other patient factors.

Patients with a cohabitant partner were significantly less likely to exhibit primary nonadherence, which may reflect higher levels of social support, including encouragement for disease self‐management and/or support with tasks such as picking up medications from the pharmacy. Previous research has demonstrated that social support mediates outpatient medication adherence for heart failure patients.[10]

Similar to Jackevicius et al., we found that patients with more medications at discharge were less likely to fill their prescriptions.[1] These findings may reflect the challenges that patients face in adhering to complex treatment plans, which are associated with increased coordination and cost. Conversely, some prior studies have found that patients with fewer prescriptions were less likely to fill.[11, 12] These patients were often younger, thus potentially less conditioned to fill prescriptions, and unlike our cohort, these populations had consistent prescription coverage. Interventions for polypharmacy, which have been shown to improve outcomes and decrease costs, especially in the geriatric population, may be of benefit for primary nonadherence as well.[13]

Additionally, patients with lower household incomes had higher rates of primary nonadherence, at least in univariate analysis. Medication cost and transportation limitations, which are more pronounced in lower‐income patients, likely play influential roles in this group. These findings build on prior literature that has found lower prescription cost to be associated with better medication adherence in a variety of settings.[3, 4, 14]

Because the prevalence of primary nonadherence in this cohort is less than half of historical rates, we suspect the intervention did reduce unintentional nonadherence. However, regimen cost and complexity, transportation challenges, and ingrained medication beliefs likely remained barriers. It may be that a postdischarge phone call is able address unintended primary nonadherence in many cases. Meds to beds programs, where a supply of medications is provided to patients prior to discharge, could assist patients with limited transportation. Prior studies have also found reduced primary nonadherence when e‐prescriptions are utilized.[3]

Establishing outpatient follow‐up at discharge provides additional opportunities to address unanticipated adherence barriers. Because the efficacy of any adherence intervention depends on individual patient barriers, we recommend combining medication counseling with a targeted approach for patient‐specific needs.

We note several limitations to our study. First, because we studied primary nonadherence that persisted despite an intervention, this cohort likely underestimates the prevalence of primary nonadherence and alters the associated patient characteristics found in routine practice (although counseling is becoming more common). Second, patient reporting is subject to biases that underestimate nonadherence, although this approach has been validated previously.[15] Third, our outcome measure was unable to capture the spectrum of non‐adherence that could provide a more nuanced look at predictors of postdischarge nonadherence. Fourth, we did not have patient copayment data to better characterize whether out of pocket costs or pharmacologic classes drove nonadherence. Finally, sample size may have limited the detection of other important factors, and the university setting may limit generalizability to cardiovascular patients in other practice environments. Future research should focus on intervention strategies that assess patients' individual adherence barriers for a targeted or multimodal approach to improve adherence.

In conclusion, we found a prevalence of primary nonadherence of almost 1 in 10 patients who received pharmacist counseling. Nonadherence was associated with being single and those discharged with longer medication lists. Our results support existing literature that primary nonadherence is a significant problem in the postdischarge setting and substantiate the need for ongoing efforts to study and implement interventions for adherence after hospital discharge.

Disclosures

This material is based on work supported by the Office of Academic Affiliations, Department of Veterans Affairs, Veterans Affairs National Quality Scholars Program, and with use of facilities at Veterans Affairs Tennessee Valley Healthcare System, Nashville, Tennessee (Dr. Wooldridge). The funding agency supported the work indirectly through provision of salary support and training for the primary author, but had no specific role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; or decision to submit the manuscript for publication. This work was also supported by R01 HL089755 (Dr. Kripalani) and in part by K23 HL077597 (Dr. Kripalani), K08 HL072806 (Dr. Schnipper), and the Center for Clinical Quality and Implementation Research at Vanderbilt University Medical Center. A preliminary version of this research was presented at the AcademyHealth Annual Research Meeting, June 16, 2015, Minneapolis, Minnesota. The authors report the following potential conflicts of interest: Jeffrey Schnipper: PI, investigator‐initiated study funded by Sanofi‐Aventis to develop, implement, and evaluate a multifaceted intervention to improve transitions of care in patients with diabetes mellitus discharged on insulin. Robert Dittus: passive co‐owner, Medical Decision Modeling, Inc.; Bayer HealthCare. One‐day consultation and panelist on educational video for population health (consultant fee); GlaxoSmithKline. One‐day consultant for population health, envisioning the future (consultant fee). Sunil Kripalani: Bioscape Digital, stock ownership

Medication nonadherence after hospital discharge impacts morbidity and mortality in patients with cardiovascular disease.[1] Primary nonadherence, part of the spectrum of medication underuse, occurs when a patient receives a prescription but does not fill it.[1] Prior studies utilizing retrospective administrative data have found a prevalence of postdischarge primary nonadherence between 24% and 28%,[1, 2] similar to findings in a variety of outpatient populations.[3, 4]

One strategy for reduction in nonadherence is discharge medication counseling, which has been associated with improved postdischarge outcomes.[1] We evaluated the prevalence and predictors of refractory primary nonadherence in a cohort of patients hospitalized for acute cardiovascular conditions who received pharmacist counseling prior to discharge to guide future adherence interventions.

METHODS

Setting and Participants

The present study represents a secondary analysis of data from the Pharmacist Intervention for Low Literacy in Cardiovascular Disease (PILL‐CVD) study. PILL‐CVD was a randomized controlled trial that evaluated the effect of a tailored intervention consisting of pharmacist‐assisted medication reconciliation, discharge counseling, low‐literacy adherence aids, and follow‐up phone calls in adults hospitalized for acute coronary syndromes or acute decompensated heart failure. Patients likely to be discharged home taking primary responsibility for their medication management were eligible. Full study methods and results, including inclusion and exclusion criteria, can be found elsewhere.[5] The institutional review boards of each site approved the study.

For the present analysis, patients were included if they had any new discharge prescriptions to fill and received the study intervention, including a postdischarge follow‐up phone call with questions about filling discharge prescriptions.

Baseline Measures

Baseline data were obtained from medical records and patient interviews, including demographic information as well as survey data for cognitive impairment (Mini‐Cog) and health literacy (Short Test of Functional Health Literacy in Adults).[6, 7]

Data were also collected related to medication use, including the number of scheduled and as‐needed medications listed at discharge, self‐reported preadmission adherence, medication understanding, and medication management practices (eg, use of a pillbox, refill reminders). Self‐reported medication adherence was measured with the 4‐item Morisky scale.[8] Medication understanding was assessed with a tool previously developed by Marvanova et al.[9]

Outcome Measures

The primary outcome was the percentage of patients who reported not filling at least 1 discharge prescription on a telephone call that was conducted 1 to 4 days postdischarge. Patients were asked a dichotomous question about whether or not they filled all of their discharge prescriptions. Further characterization of the class or number of medications not filled was not performed. Patients were asked to provide a reason for not filling the prescriptions.

Analysis

We evaluated the prevalence and possible predictors of primary nonadherence including age, gender, race, marital status, education and income levels, insurance type, health literacy, cognition, presence of a primary care physician, number of listed discharge medications, prehospital medication adherence, medication understanding, and medication management practices using Pearson 2, Fisher exact, or Wilcoxon rank sum tests as appropriate. Multiple logistic regression with backward elimination was performed to identify independent predictors, selected with P values<0.1. We also evaluated reasons that patients cited for not filling prescriptions. Two‐sided P values<0.05 were considered statistically significant. All analyses were conducted using Stata version 13.1 (StataCorp LP, College Station, TX).

RESULTS

Of 851 patients in the PILL‐CVD study, the present sample includes 341 patients who received the intervention, completed the postdischarge follow‐up call, and had new discharge prescriptions to be filled. This represents 85% of patients who received the intervention.

The mean age of participants was 61.3 years, and 59.5% were male (Table 1). The majority were white (75.1%), and 88% had at least a high school education. Married or cohabitating patients represented 54.3% of the group. Just over half of the patients (54%) had an income of $35K or greater. The primary source of insurance for 82.5% of patients was either Medicare or private insurance, and 7.4% of patients were self‐pay. Most patients (80%) had adequate health literacy. The median Mini‐Cog score was 4 out of 5 (interquartile range [IQR]=35), and 11% of patients had scores indicating cognitive impairment. Just less than one‐fourth of the patients (24.1%) had a Morisky score of 8, indicating high self‐reported adherence, and the median score of patients' understanding of medications (range of 03) was 2.5 (IQR=2.22.8), reflecting relatively high understanding. The median number of prescriptions on patients' discharge medications lists was 10 (IQR=813).

Patient Characteristics
Variable Overall 341 (100.0%) Filled Prescription309 (90.6%) Did Not Fill 32 (9.4%) P Value
  • NOTE: Missing values are present in the following categories: race (n=3), income (n=28), insurance (n=5).

  • Pearson 2 test.

  • P<0.05.

  • Fisher exact test (2‐sided).

Age, y, N (%) 0.745a
1849 69 63 (91.3) 6 (8.7)
5064 128 114 (89.1) 14 (10.9)
65+ 144 132 (91.7) 12 (8.3)
Gender, N (%) 0.056a
Male 203 189 (93.1) 14 (6.9)
Female 138 120 (87.0) 18 (13.0)
Race, N (%) 0.712a
White 256 234 (91.4) 22 (8.6)
African American 60 54 (90.0) 6 (10.0)
Other 22 19 (86.4) 3 (13.6)
Education, N (%) 0.054a
Less than high school 40 32 (80.0) 8 (20.0)
High school 99 91 (91.9) 8 (8.1)
1315 years 93 83 (89.2) 10 (10.8)
16 years 109 103 (94.5) 6 (5.5)
Marital status, N (%)
Separated/divorced/widowed/never married 156 135 (86.5) 21 (13.5) 0.018a, b
Married/cohabitating 185 174 (94.1) 11 (5.9)
Income, N (%) 0.040a, b
<10K<20K 58 48 (82.8) 10 (17.2)
20K35K 86 76 (88.4) 10 (11.6)
35K<50K 40 36 (90.0) 4 (10.0)
50K<75K 46 43 (93.5) 3 (6.5)
75K+ 83 81 (97.6) 2 (2.4)
Primary source of payment, N (%) 0.272a
Medicaid 34 28 (82.4) 6 (17.6)
Medicare 145 131 (90.3) 14 (9.7)
Private 132 123 (93.2) 9 (6.8)
Self‐pay 25 22 (88.0) 3 (12.0)
Primary care physician, N (%) 1.000c
None/do not know 28 26 (92.9) 2 (7.1)
Yes 313 283 (90.4) 30 (9.6)
Site, N (%) 0.071a
Nashville, TN 172 151 (87.8) 21 (12.2)
Boston, MA 169 158 (93.5) 11 (6.5)

The prevalence of refractory primary nonadherence was 9.4%. In univariate analysis, single marital status, lower income, and having more than 10 total discharge medications were significantly associated with not filling medications (P=0.018, 0.04, 0.016, respectively; Table 1). In multivariable analysis, single marital status and having more than 10 total discharge medications maintained significance when controlling for other patient characteristics. Patients who were single had higher odds of failing to fill discharge prescriptions compared to married or cohabitating individuals (odds ratio [OR]: 2.2, 95% confidence interval [CI]: 1.014.8, P=0.047). Patients with more than 10 discharge medications also had higher odds of failing to fill compared with patients who had fewer total medications (OR: 2.3, 95% CI: 1.054.98, P=0.036).

Filling discharge prescriptions was not associated with health literacy, cognition, prehospital adherence, patients' medication understanding, or any of the surveyed medication management practices (Table 2). Patients' reasons for not filling included lack of time to go to the pharmacy, medications not being delivered or dispensed, or inability to afford prescriptions. Prescription cost was cited by 23.5% of patients who did not fill their prescriptions and provided a reason.

Patient Medication‐Related Characteristics
Variable Overall 341 (100.0%) Filled Prescription 309 (90.6%) Did Not Fill 32 (9.4%) P Value
  • NOTE: Missing values are present in the following categories: s‐TOFHLA (n=6), Morisky (n=13). Abbreviations: s‐TOFHLA, Short Test of Functional Health Literacy in Adults.

  • Pearson 2 test.

  • Fisher exact test (2‐sided).

  • Number on discharge medication list.

s‐TOFHLA score, range 036, N (%) 0.443a
Inadequate, 016 40 34 (85.0) 6 (15.0)
Marginal, 1722 27 25 (92.6) 2 (7.4)
Adequate, 2336 268 244 (91.0) 24 (9.0)
MiniCog score, range 05, N (%) 0.764b
Not impaired, 35 304 276 (90.8) 28 (9.2)
Impaired, 02 37 33 (89.2) 4 (10.8)
Morisky score, range 48, N (%) 0.517a
Low/moderate self‐reported adherence, 47 249 224 (90.0) 25 (10.0)
High self‐reported adherence, 8 79 73 (92.4) 6 (7.6)
No. of discharge medications, range 126, N (%)c 0.016a
010 medications 186 175 (94.1) 11 (5.9)
11+medications 155 134 (86.5) 21 (13.5)
Patient responses to medication behavior questions
Patient associates medication taking time with daily events 253 229 (90.5) 24 (9.5) 0.913a
Patient uses a pillbox to organize medicine 180 162 (90.0) 18 (10.0) 0.680a
Friends of family help remind patient when it is time to take medicine 89 79 (88.8) 10 (11.2) 0.486a
Patient writes down instructions for when to take medicine 60 55 (91.7) 5 (8.3) 0.758a
Patient uses an alarm or a reminder that beeps when it is time to take medicine 8 6 (75.0) 2 (25.0) 0.167a
Patient marks refill date on calendar 38 35 (92.1) 3 (7.9) 1.000b
Pharmacy gives or sends patient a reminder when it is time to refill medicine 94 84 (89.4) 10 (10.6) 0.624a
Friends or family help patient to refill medicine 60 53 (88.3) 7 (11.7) 0.504a

DISCUSSION

Almost 1 in 10 patients hospitalized with cardiovascular disease demonstrated primary nonadherence refractory to an intervention including pharmacist discharge medication counseling. Being unmarried and having greater than 10 medications at discharge were significantly associated with higher primary nonadherence when controlling for other patient factors.

Patients with a cohabitant partner were significantly less likely to exhibit primary nonadherence, which may reflect higher levels of social support, including encouragement for disease self‐management and/or support with tasks such as picking up medications from the pharmacy. Previous research has demonstrated that social support mediates outpatient medication adherence for heart failure patients.[10]

Similar to Jackevicius et al., we found that patients with more medications at discharge were less likely to fill their prescriptions.[1] These findings may reflect the challenges that patients face in adhering to complex treatment plans, which are associated with increased coordination and cost. Conversely, some prior studies have found that patients with fewer prescriptions were less likely to fill.[11, 12] These patients were often younger, thus potentially less conditioned to fill prescriptions, and unlike our cohort, these populations had consistent prescription coverage. Interventions for polypharmacy, which have been shown to improve outcomes and decrease costs, especially in the geriatric population, may be of benefit for primary nonadherence as well.[13]

Additionally, patients with lower household incomes had higher rates of primary nonadherence, at least in univariate analysis. Medication cost and transportation limitations, which are more pronounced in lower‐income patients, likely play influential roles in this group. These findings build on prior literature that has found lower prescription cost to be associated with better medication adherence in a variety of settings.[3, 4, 14]

Because the prevalence of primary nonadherence in this cohort is less than half of historical rates, we suspect the intervention did reduce unintentional nonadherence. However, regimen cost and complexity, transportation challenges, and ingrained medication beliefs likely remained barriers. It may be that a postdischarge phone call is able address unintended primary nonadherence in many cases. Meds to beds programs, where a supply of medications is provided to patients prior to discharge, could assist patients with limited transportation. Prior studies have also found reduced primary nonadherence when e‐prescriptions are utilized.[3]

Establishing outpatient follow‐up at discharge provides additional opportunities to address unanticipated adherence barriers. Because the efficacy of any adherence intervention depends on individual patient barriers, we recommend combining medication counseling with a targeted approach for patient‐specific needs.

We note several limitations to our study. First, because we studied primary nonadherence that persisted despite an intervention, this cohort likely underestimates the prevalence of primary nonadherence and alters the associated patient characteristics found in routine practice (although counseling is becoming more common). Second, patient reporting is subject to biases that underestimate nonadherence, although this approach has been validated previously.[15] Third, our outcome measure was unable to capture the spectrum of non‐adherence that could provide a more nuanced look at predictors of postdischarge nonadherence. Fourth, we did not have patient copayment data to better characterize whether out of pocket costs or pharmacologic classes drove nonadherence. Finally, sample size may have limited the detection of other important factors, and the university setting may limit generalizability to cardiovascular patients in other practice environments. Future research should focus on intervention strategies that assess patients' individual adherence barriers for a targeted or multimodal approach to improve adherence.

In conclusion, we found a prevalence of primary nonadherence of almost 1 in 10 patients who received pharmacist counseling. Nonadherence was associated with being single and those discharged with longer medication lists. Our results support existing literature that primary nonadherence is a significant problem in the postdischarge setting and substantiate the need for ongoing efforts to study and implement interventions for adherence after hospital discharge.

Disclosures

This material is based on work supported by the Office of Academic Affiliations, Department of Veterans Affairs, Veterans Affairs National Quality Scholars Program, and with use of facilities at Veterans Affairs Tennessee Valley Healthcare System, Nashville, Tennessee (Dr. Wooldridge). The funding agency supported the work indirectly through provision of salary support and training for the primary author, but had no specific role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; or decision to submit the manuscript for publication. This work was also supported by R01 HL089755 (Dr. Kripalani) and in part by K23 HL077597 (Dr. Kripalani), K08 HL072806 (Dr. Schnipper), and the Center for Clinical Quality and Implementation Research at Vanderbilt University Medical Center. A preliminary version of this research was presented at the AcademyHealth Annual Research Meeting, June 16, 2015, Minneapolis, Minnesota. The authors report the following potential conflicts of interest: Jeffrey Schnipper: PI, investigator‐initiated study funded by Sanofi‐Aventis to develop, implement, and evaluate a multifaceted intervention to improve transitions of care in patients with diabetes mellitus discharged on insulin. Robert Dittus: passive co‐owner, Medical Decision Modeling, Inc.; Bayer HealthCare. One‐day consultation and panelist on educational video for population health (consultant fee); GlaxoSmithKline. One‐day consultant for population health, envisioning the future (consultant fee). Sunil Kripalani: Bioscape Digital, stock ownership

References
  1. Jackevicius CA, Li P, Tu JV. Prevalence, predictors, and outcomes of primary nonadherence after acute myocardial infarction. Circulation. 2008;117(8):10281036.
  2. Fallis BA, Dhalla IA, Klemensberg J, Bell CM. Primary medication non‐adherence after discharge from a general internal medicine service. PloS One. 2013;8(5):e61735.
  3. Fischer MA, Choudhry NK, Brill G, et al. Trouble getting started: predictors of primary medication nonadherence. Am J Med. 2011;124(11):1081.e9–22.
  4. Tamblyn R, Eguale T, Huang A, Winslade N, Doran P. The incidence and determinants of primary nonadherence with prescribed medication in primary care: a cohort study. Ann Intern Med. 2014;160(7):441450.
  5. Kripalani S, Roumie CL, Dalal AK, et al. Effect of a pharmacist intervention on clinically important medication errors after hospital discharge: a randomized trial. Ann Intern Med. 2012;157(1):110.
  6. Nurss J, Parker R, Williams M, Baker D. Short Test of Functional Health Literacy in Adults. Snow Camp, NC: Peppercorn Books and Press; 1998.
  7. Borson S, Scanlan JM, Watanabe J, Tu SP, Lessig M. Simplifying detection of cognitive impairment: comparison of the Mini‐Cog and Mini‐Mental State Examination in a multiethnic sample. J Am Geriatr Soc. 2005;53(5):871874.
  8. Morisky DE, Green LW, Levine DM. Concurrent and predictive validity of a self‐reported measure of medication adherence. Med Care. 1986;24(1):6774.
  9. Marvanova M, Roumie CL, Eden SK, Cawthon C, Schnipper JL, Kripalani S. Health literacy and medication understanding among hospitalized adults. J Hosp Med. 2011;6(9):488493.
  10. Wu JR, Frazier SK, Rayens MK, Lennie TA, Chung ML, Moser DK. Medication adherence, social support, and event‐free survival in patients with heart failure. Health Psychol. 2013;32(6):637646.
  11. Lagu T, Weiner MG, Eachus S, Tang SS, Schwartz JS, Turner BJ. Effect of patient comorbidities on filling of antihypertensive prescriptions. Am J Manag Care. 2009;15(1):2430.
  12. Cheetham TC, Niu F, Green K, et al. Primary nonadherence to statin medications in a managed care organization. J Manag Care Pharm. 2013;19(5):367373.
  13. Kojima G, Bell C, Tamura B, et al. Reducing cost by reducing polypharmacy: the polypharmacy outcomes project. J Am Med Dir Assoc. 2012;13(9):818.e811–815.
  14. Shrank WH, Choudhry NK, Fischer MA, et al. The epidemiology of prescriptions abandoned at the pharmacy. Ann Intern Med. 2010;153(10):633640.
  15. Haynes RB, Taylor DW, Sackett DL, Gibson ES, Bernholz CD, Mukherjee J. Can simple clinical measurements detect patient noncompliance? Hypertension. 1980;2(6):757764.
References
  1. Jackevicius CA, Li P, Tu JV. Prevalence, predictors, and outcomes of primary nonadherence after acute myocardial infarction. Circulation. 2008;117(8):10281036.
  2. Fallis BA, Dhalla IA, Klemensberg J, Bell CM. Primary medication non‐adherence after discharge from a general internal medicine service. PloS One. 2013;8(5):e61735.
  3. Fischer MA, Choudhry NK, Brill G, et al. Trouble getting started: predictors of primary medication nonadherence. Am J Med. 2011;124(11):1081.e9–22.
  4. Tamblyn R, Eguale T, Huang A, Winslade N, Doran P. The incidence and determinants of primary nonadherence with prescribed medication in primary care: a cohort study. Ann Intern Med. 2014;160(7):441450.
  5. Kripalani S, Roumie CL, Dalal AK, et al. Effect of a pharmacist intervention on clinically important medication errors after hospital discharge: a randomized trial. Ann Intern Med. 2012;157(1):110.
  6. Nurss J, Parker R, Williams M, Baker D. Short Test of Functional Health Literacy in Adults. Snow Camp, NC: Peppercorn Books and Press; 1998.
  7. Borson S, Scanlan JM, Watanabe J, Tu SP, Lessig M. Simplifying detection of cognitive impairment: comparison of the Mini‐Cog and Mini‐Mental State Examination in a multiethnic sample. J Am Geriatr Soc. 2005;53(5):871874.
  8. Morisky DE, Green LW, Levine DM. Concurrent and predictive validity of a self‐reported measure of medication adherence. Med Care. 1986;24(1):6774.
  9. Marvanova M, Roumie CL, Eden SK, Cawthon C, Schnipper JL, Kripalani S. Health literacy and medication understanding among hospitalized adults. J Hosp Med. 2011;6(9):488493.
  10. Wu JR, Frazier SK, Rayens MK, Lennie TA, Chung ML, Moser DK. Medication adherence, social support, and event‐free survival in patients with heart failure. Health Psychol. 2013;32(6):637646.
  11. Lagu T, Weiner MG, Eachus S, Tang SS, Schwartz JS, Turner BJ. Effect of patient comorbidities on filling of antihypertensive prescriptions. Am J Manag Care. 2009;15(1):2430.
  12. Cheetham TC, Niu F, Green K, et al. Primary nonadherence to statin medications in a managed care organization. J Manag Care Pharm. 2013;19(5):367373.
  13. Kojima G, Bell C, Tamura B, et al. Reducing cost by reducing polypharmacy: the polypharmacy outcomes project. J Am Med Dir Assoc. 2012;13(9):818.e811–815.
  14. Shrank WH, Choudhry NK, Fischer MA, et al. The epidemiology of prescriptions abandoned at the pharmacy. Ann Intern Med. 2010;153(10):633640.
  15. Haynes RB, Taylor DW, Sackett DL, Gibson ES, Bernholz CD, Mukherjee J. Can simple clinical measurements detect patient noncompliance? Hypertension. 1980;2(6):757764.
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The modern physician-communicator

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The modern physician-communicator

Forty years ago, the revered physician was a walking textbook able to recall vast amounts of information. Things have changed. A photographic memory is less valuable since Google was created. Medical knowledge has a much shorter shelf life. Specialization has become increasingly fragmented. The orthopedic surgeon who replaced my hip 5 years ago would not see me for a shoulder problem. He only does hips and knees. Ingrown toenails are referred to a podiatrist. Now the ideal physician is a team player able to communicate well with many other physicians and allied health care providers so that the patches of individual expertise combine to create a quilt that covers the patient’s needs. Poor communicators are like odd-shaped and frayed pieces of fabric that are hard to fit into the quilt.

Medical errors were identified by the Institute of Medicine (IOM) in 1999 as a major cause of preventable deaths. What has become clear in research since then is that most of these errors are not caused by deficits in knowledge or to carelessness. They are partly because of communication skills and because of attitudes that impede collaborative comanagement. Errors are mostly systemic problems and should be addressed in that paradigm.

Since that first IOM report, several other areas have been identified as major causes of preventable deaths in hospitals. These problems include nosocomial infections, antibiotic stewardship, medication list reconciliation, overdiagnosis, and the handoff of care at discharge (N Engl J Med. 2014 Nov 6;371[19]:1803-12). The lack of a cure for Ebola is a minor problem, compared with these weaknesses in the hospital care system. Too much futile care and the delay of palliative care also are frequent problems, more so with adults than pediatrics. Pediatric hospitalists have been more focused on value (Pediatrics 2015 Aug 1. [doi: 10.1542/peds.2015-1549A]).

Most of these issues were never discussed in the pathophysiology courses of medical school. They are outside the biological sciences. As a result, it has become a major part of graduate Continuing Medical Education. The schedule for the recent Pediatric Hospital Medicine 2015 conference reflects this. The 830 attendees could choose from 12 simultaneous breakout sessions, but typically only 3 or 4 were primarily about clinical medicine. Quality improvement, education, research, and practice management made up the lion’s share of the topics.

This emphasis on systems is the core of hospital medicine. It isn’t about knowing which antibiotic is best for a given patient with a particular pneumonia because usually we don’t know the organism. It is about saying, “We will admit 300 patients with pneumonia to this hospital this year. What are best practices?” In pediatrics, many pneumonias will be viral. The vast majority of bacterial pneumonia will be pneumococcal. Staphylococcus aureus is involved in less than 1% and most of those cases present differently. So what criteria do we use to determine who gets narrow-spectrum antibiotics, who gets broad spectrum, who gets mycoplasma coverage, and who gets supportive care without unnecessary antibiotics? Practice guidelines for the provision of oxygen, intravenous fluids, and the use of continuous pulse oximetry monitoring each were covered in other presentations at the 2015 pediatric hospitalist meeting. More importantly, as Dr. Brian K. Alverson, director, division of pediatric hospital medicine, Hasbro Children’s Hospital in Providence, R.I., explained, guidelines are meant to cover only 95% of patients. It is the job of the patient’s physician to decide whether that patient fits into the 95% or is one of the 5% who need customized, less evidence-based plans of care. Perhaps most importantly, the guidelines themselves are undergoing continuous quality improvement. The Infectious Diseases Society of American (IDSA) guidelines for pediatric community-acquired pneumonia were published just 4 years ago, but already have recommendations that are refuted by more recent research.

Author Robert Fulghum is right. Most of the lessons I learned in kindergarten are still applicable. Medical school – not so much.

Dr. Powell is a pediatric hospitalist and clinical ethics consultant living in St. Louis. Email him at pdnews@frontlinemedcom.com. Dr. Powell said he had no relevant financial disclosures.

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Forty years ago, the revered physician was a walking textbook able to recall vast amounts of information. Things have changed. A photographic memory is less valuable since Google was created. Medical knowledge has a much shorter shelf life. Specialization has become increasingly fragmented. The orthopedic surgeon who replaced my hip 5 years ago would not see me for a shoulder problem. He only does hips and knees. Ingrown toenails are referred to a podiatrist. Now the ideal physician is a team player able to communicate well with many other physicians and allied health care providers so that the patches of individual expertise combine to create a quilt that covers the patient’s needs. Poor communicators are like odd-shaped and frayed pieces of fabric that are hard to fit into the quilt.

Medical errors were identified by the Institute of Medicine (IOM) in 1999 as a major cause of preventable deaths. What has become clear in research since then is that most of these errors are not caused by deficits in knowledge or to carelessness. They are partly because of communication skills and because of attitudes that impede collaborative comanagement. Errors are mostly systemic problems and should be addressed in that paradigm.

Since that first IOM report, several other areas have been identified as major causes of preventable deaths in hospitals. These problems include nosocomial infections, antibiotic stewardship, medication list reconciliation, overdiagnosis, and the handoff of care at discharge (N Engl J Med. 2014 Nov 6;371[19]:1803-12). The lack of a cure for Ebola is a minor problem, compared with these weaknesses in the hospital care system. Too much futile care and the delay of palliative care also are frequent problems, more so with adults than pediatrics. Pediatric hospitalists have been more focused on value (Pediatrics 2015 Aug 1. [doi: 10.1542/peds.2015-1549A]).

Most of these issues were never discussed in the pathophysiology courses of medical school. They are outside the biological sciences. As a result, it has become a major part of graduate Continuing Medical Education. The schedule for the recent Pediatric Hospital Medicine 2015 conference reflects this. The 830 attendees could choose from 12 simultaneous breakout sessions, but typically only 3 or 4 were primarily about clinical medicine. Quality improvement, education, research, and practice management made up the lion’s share of the topics.

This emphasis on systems is the core of hospital medicine. It isn’t about knowing which antibiotic is best for a given patient with a particular pneumonia because usually we don’t know the organism. It is about saying, “We will admit 300 patients with pneumonia to this hospital this year. What are best practices?” In pediatrics, many pneumonias will be viral. The vast majority of bacterial pneumonia will be pneumococcal. Staphylococcus aureus is involved in less than 1% and most of those cases present differently. So what criteria do we use to determine who gets narrow-spectrum antibiotics, who gets broad spectrum, who gets mycoplasma coverage, and who gets supportive care without unnecessary antibiotics? Practice guidelines for the provision of oxygen, intravenous fluids, and the use of continuous pulse oximetry monitoring each were covered in other presentations at the 2015 pediatric hospitalist meeting. More importantly, as Dr. Brian K. Alverson, director, division of pediatric hospital medicine, Hasbro Children’s Hospital in Providence, R.I., explained, guidelines are meant to cover only 95% of patients. It is the job of the patient’s physician to decide whether that patient fits into the 95% or is one of the 5% who need customized, less evidence-based plans of care. Perhaps most importantly, the guidelines themselves are undergoing continuous quality improvement. The Infectious Diseases Society of American (IDSA) guidelines for pediatric community-acquired pneumonia were published just 4 years ago, but already have recommendations that are refuted by more recent research.

Author Robert Fulghum is right. Most of the lessons I learned in kindergarten are still applicable. Medical school – not so much.

Dr. Powell is a pediatric hospitalist and clinical ethics consultant living in St. Louis. Email him at pdnews@frontlinemedcom.com. Dr. Powell said he had no relevant financial disclosures.

Forty years ago, the revered physician was a walking textbook able to recall vast amounts of information. Things have changed. A photographic memory is less valuable since Google was created. Medical knowledge has a much shorter shelf life. Specialization has become increasingly fragmented. The orthopedic surgeon who replaced my hip 5 years ago would not see me for a shoulder problem. He only does hips and knees. Ingrown toenails are referred to a podiatrist. Now the ideal physician is a team player able to communicate well with many other physicians and allied health care providers so that the patches of individual expertise combine to create a quilt that covers the patient’s needs. Poor communicators are like odd-shaped and frayed pieces of fabric that are hard to fit into the quilt.

Medical errors were identified by the Institute of Medicine (IOM) in 1999 as a major cause of preventable deaths. What has become clear in research since then is that most of these errors are not caused by deficits in knowledge or to carelessness. They are partly because of communication skills and because of attitudes that impede collaborative comanagement. Errors are mostly systemic problems and should be addressed in that paradigm.

Since that first IOM report, several other areas have been identified as major causes of preventable deaths in hospitals. These problems include nosocomial infections, antibiotic stewardship, medication list reconciliation, overdiagnosis, and the handoff of care at discharge (N Engl J Med. 2014 Nov 6;371[19]:1803-12). The lack of a cure for Ebola is a minor problem, compared with these weaknesses in the hospital care system. Too much futile care and the delay of palliative care also are frequent problems, more so with adults than pediatrics. Pediatric hospitalists have been more focused on value (Pediatrics 2015 Aug 1. [doi: 10.1542/peds.2015-1549A]).

Most of these issues were never discussed in the pathophysiology courses of medical school. They are outside the biological sciences. As a result, it has become a major part of graduate Continuing Medical Education. The schedule for the recent Pediatric Hospital Medicine 2015 conference reflects this. The 830 attendees could choose from 12 simultaneous breakout sessions, but typically only 3 or 4 were primarily about clinical medicine. Quality improvement, education, research, and practice management made up the lion’s share of the topics.

This emphasis on systems is the core of hospital medicine. It isn’t about knowing which antibiotic is best for a given patient with a particular pneumonia because usually we don’t know the organism. It is about saying, “We will admit 300 patients with pneumonia to this hospital this year. What are best practices?” In pediatrics, many pneumonias will be viral. The vast majority of bacterial pneumonia will be pneumococcal. Staphylococcus aureus is involved in less than 1% and most of those cases present differently. So what criteria do we use to determine who gets narrow-spectrum antibiotics, who gets broad spectrum, who gets mycoplasma coverage, and who gets supportive care without unnecessary antibiotics? Practice guidelines for the provision of oxygen, intravenous fluids, and the use of continuous pulse oximetry monitoring each were covered in other presentations at the 2015 pediatric hospitalist meeting. More importantly, as Dr. Brian K. Alverson, director, division of pediatric hospital medicine, Hasbro Children’s Hospital in Providence, R.I., explained, guidelines are meant to cover only 95% of patients. It is the job of the patient’s physician to decide whether that patient fits into the 95% or is one of the 5% who need customized, less evidence-based plans of care. Perhaps most importantly, the guidelines themselves are undergoing continuous quality improvement. The Infectious Diseases Society of American (IDSA) guidelines for pediatric community-acquired pneumonia were published just 4 years ago, but already have recommendations that are refuted by more recent research.

Author Robert Fulghum is right. Most of the lessons I learned in kindergarten are still applicable. Medical school – not so much.

Dr. Powell is a pediatric hospitalist and clinical ethics consultant living in St. Louis. Email him at pdnews@frontlinemedcom.com. Dr. Powell said he had no relevant financial disclosures.

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Selective eating

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You may not have read the much ballyhooed article about selective eating in preschoolers that was distributed to the media prior to publication because it was buried online, but I bet that you have heard or read something about it (“Psychological and Psychosocial Impairment in Preschoolers with Selective Eating” by Zucker et al., [Pediatrics. 2015 Aug 3. doi: 10.1542/peds.2014-2386]). In fact, there were so many news stories, both print and electronic, and the headlines were so divergent that my wife asked me if there were actually two studies released simultaneously.

Some news reports emphasized the reassuring observation by the authors that most picky eating preschoolers will mature into older children with less selective eating habits. However, others highlighted the authors’ primary message that young children with severe selective eating behavior often have significant psychopathology (anxiety, depression, attention-deficit/hyperactivity disorder), and those with even moderate picky eating may be manifesting the effects of living in a dysfunctional family.

Dr. William G. Wilkoff

The authors recommend that we pediatricians rethink our traditional party line on selective eating. Instead of simply administering frequent doses of reassurance to the parents of “picky eaters,” we should begin to view even moderate selective eating as a red flag that the child and his or her family need help.

This shift in emphasis is long overdue. I always have felt that problem picky eating is an example of normal infant behavior that has been mismanaged by the child’s family. And in some cases physicians also must share in the blame for not having given the most appropriate advice in a timely fashion to parents who have complained about their child’s selective eating.

It would help if we all took a deep breath, stepped back a few steps, and looked at the bigger picture. We are talking about eating, one of the critical life-sustaining activities. One can understand why most infants are wired to initially reject new tastes and textures. Neophobia – fear of anything new – has probably saved millions of infants from the serious consequences of unsupervised foraging. But don’t you think that these aversions are for the most part weak enough to be easily overridden by every child’s innate drive for self-preservation? “I don’t like how this smells, tastes, looks, or feels, but darn it, I’m getting hungry, and I have to eat to survive. So I will eat it.”

The problem is that while some parents can agree with that line of reasoning, many parents, including those who buy the rationale, can’t bring themselves to quietly accept their new role as merely being providers of a healthy diet. For 9 or 10 months, it was their job to get food into their child because the poor little thing lacked the skill to do it himself. But once a child can chew solids and put things in his mouth, he can not only survive but thrive if someone will simply present him a balanced diet of appropriate consistency and volume … and then step back and shut up.

Obviously, this transition is difficult to a significant number of parents. In many cases, it is because no one has told them that toddlers will appear to eat less than they did as infants or that allowing children unlimited access to energy-containing fluid will blunt their appetites. Or that it is okay that a child only eats one-and-a-half meals on some days. Or that it if you wait long enough without resorting to coaxing, bribing, or begging, a child will eat what his body needs. And failing to be patient and instead making an issue of eating (or not eating), what began as a normal infant aversion to new tastes and textures can spiral into a divisive family catastrophe.

Are there some infants who are so hypersensitive to new tastes and textures that waiting will endanger their health? If they exist, in my experience they are very rare. However, there are certainly toddlers who have become hypersensitive. In my opinion, they were always vulnerable and would have been much less of a problem had they been properly managed early on when they were just a little neophobic.

Are there clues during the child’s infancy that his family is more likely to have significant difficulty making the transition from “feeding” to “presenting” food? This new study observed that high maternal anxiety was frequently observed in both moderate and severe selective-eating children. This is another example of how we need to be aware from a very early stage when a parent is anxious or depressed. The failure to identify and see that those issues are addressed can seriously impair the whole family’s wellness.

 

 

Finally, on the other end of the spectrum, is usual garden variety selective eating outgrown? Have you tried to host a dinner party lately? I don’t mean a pot luck supper – I’m talking about a sit-down meal with a single menu. My wife and I have almost given up trying. “Martha is gluten free (without a diagnosis), Bob is watching his cholesterol, Rachel is pretty sure she is lactose intolerant, and you know Charlie hates vegetables. The Wilsons only do organic and are vegetarians.”

Next time we are considering mailing them gift certificates for their favorite restaurants along with an invitation to come over to our place for an after dinner drink. BYOB.

Dr. Wilkoff practiced primary care pediatrics in Brunswick, Maine, for nearly 40 years. He has authored several books on behavioral pediatrics, including “Coping with a Picky Eater.”

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You may not have read the much ballyhooed article about selective eating in preschoolers that was distributed to the media prior to publication because it was buried online, but I bet that you have heard or read something about it (“Psychological and Psychosocial Impairment in Preschoolers with Selective Eating” by Zucker et al., [Pediatrics. 2015 Aug 3. doi: 10.1542/peds.2014-2386]). In fact, there were so many news stories, both print and electronic, and the headlines were so divergent that my wife asked me if there were actually two studies released simultaneously.

Some news reports emphasized the reassuring observation by the authors that most picky eating preschoolers will mature into older children with less selective eating habits. However, others highlighted the authors’ primary message that young children with severe selective eating behavior often have significant psychopathology (anxiety, depression, attention-deficit/hyperactivity disorder), and those with even moderate picky eating may be manifesting the effects of living in a dysfunctional family.

Dr. William G. Wilkoff

The authors recommend that we pediatricians rethink our traditional party line on selective eating. Instead of simply administering frequent doses of reassurance to the parents of “picky eaters,” we should begin to view even moderate selective eating as a red flag that the child and his or her family need help.

This shift in emphasis is long overdue. I always have felt that problem picky eating is an example of normal infant behavior that has been mismanaged by the child’s family. And in some cases physicians also must share in the blame for not having given the most appropriate advice in a timely fashion to parents who have complained about their child’s selective eating.

It would help if we all took a deep breath, stepped back a few steps, and looked at the bigger picture. We are talking about eating, one of the critical life-sustaining activities. One can understand why most infants are wired to initially reject new tastes and textures. Neophobia – fear of anything new – has probably saved millions of infants from the serious consequences of unsupervised foraging. But don’t you think that these aversions are for the most part weak enough to be easily overridden by every child’s innate drive for self-preservation? “I don’t like how this smells, tastes, looks, or feels, but darn it, I’m getting hungry, and I have to eat to survive. So I will eat it.”

The problem is that while some parents can agree with that line of reasoning, many parents, including those who buy the rationale, can’t bring themselves to quietly accept their new role as merely being providers of a healthy diet. For 9 or 10 months, it was their job to get food into their child because the poor little thing lacked the skill to do it himself. But once a child can chew solids and put things in his mouth, he can not only survive but thrive if someone will simply present him a balanced diet of appropriate consistency and volume … and then step back and shut up.

Obviously, this transition is difficult to a significant number of parents. In many cases, it is because no one has told them that toddlers will appear to eat less than they did as infants or that allowing children unlimited access to energy-containing fluid will blunt their appetites. Or that it is okay that a child only eats one-and-a-half meals on some days. Or that it if you wait long enough without resorting to coaxing, bribing, or begging, a child will eat what his body needs. And failing to be patient and instead making an issue of eating (or not eating), what began as a normal infant aversion to new tastes and textures can spiral into a divisive family catastrophe.

Are there some infants who are so hypersensitive to new tastes and textures that waiting will endanger their health? If they exist, in my experience they are very rare. However, there are certainly toddlers who have become hypersensitive. In my opinion, they were always vulnerable and would have been much less of a problem had they been properly managed early on when they were just a little neophobic.

Are there clues during the child’s infancy that his family is more likely to have significant difficulty making the transition from “feeding” to “presenting” food? This new study observed that high maternal anxiety was frequently observed in both moderate and severe selective-eating children. This is another example of how we need to be aware from a very early stage when a parent is anxious or depressed. The failure to identify and see that those issues are addressed can seriously impair the whole family’s wellness.

 

 

Finally, on the other end of the spectrum, is usual garden variety selective eating outgrown? Have you tried to host a dinner party lately? I don’t mean a pot luck supper – I’m talking about a sit-down meal with a single menu. My wife and I have almost given up trying. “Martha is gluten free (without a diagnosis), Bob is watching his cholesterol, Rachel is pretty sure she is lactose intolerant, and you know Charlie hates vegetables. The Wilsons only do organic and are vegetarians.”

Next time we are considering mailing them gift certificates for their favorite restaurants along with an invitation to come over to our place for an after dinner drink. BYOB.

Dr. Wilkoff practiced primary care pediatrics in Brunswick, Maine, for nearly 40 years. He has authored several books on behavioral pediatrics, including “Coping with a Picky Eater.”

You may not have read the much ballyhooed article about selective eating in preschoolers that was distributed to the media prior to publication because it was buried online, but I bet that you have heard or read something about it (“Psychological and Psychosocial Impairment in Preschoolers with Selective Eating” by Zucker et al., [Pediatrics. 2015 Aug 3. doi: 10.1542/peds.2014-2386]). In fact, there were so many news stories, both print and electronic, and the headlines were so divergent that my wife asked me if there were actually two studies released simultaneously.

Some news reports emphasized the reassuring observation by the authors that most picky eating preschoolers will mature into older children with less selective eating habits. However, others highlighted the authors’ primary message that young children with severe selective eating behavior often have significant psychopathology (anxiety, depression, attention-deficit/hyperactivity disorder), and those with even moderate picky eating may be manifesting the effects of living in a dysfunctional family.

Dr. William G. Wilkoff

The authors recommend that we pediatricians rethink our traditional party line on selective eating. Instead of simply administering frequent doses of reassurance to the parents of “picky eaters,” we should begin to view even moderate selective eating as a red flag that the child and his or her family need help.

This shift in emphasis is long overdue. I always have felt that problem picky eating is an example of normal infant behavior that has been mismanaged by the child’s family. And in some cases physicians also must share in the blame for not having given the most appropriate advice in a timely fashion to parents who have complained about their child’s selective eating.

It would help if we all took a deep breath, stepped back a few steps, and looked at the bigger picture. We are talking about eating, one of the critical life-sustaining activities. One can understand why most infants are wired to initially reject new tastes and textures. Neophobia – fear of anything new – has probably saved millions of infants from the serious consequences of unsupervised foraging. But don’t you think that these aversions are for the most part weak enough to be easily overridden by every child’s innate drive for self-preservation? “I don’t like how this smells, tastes, looks, or feels, but darn it, I’m getting hungry, and I have to eat to survive. So I will eat it.”

The problem is that while some parents can agree with that line of reasoning, many parents, including those who buy the rationale, can’t bring themselves to quietly accept their new role as merely being providers of a healthy diet. For 9 or 10 months, it was their job to get food into their child because the poor little thing lacked the skill to do it himself. But once a child can chew solids and put things in his mouth, he can not only survive but thrive if someone will simply present him a balanced diet of appropriate consistency and volume … and then step back and shut up.

Obviously, this transition is difficult to a significant number of parents. In many cases, it is because no one has told them that toddlers will appear to eat less than they did as infants or that allowing children unlimited access to energy-containing fluid will blunt their appetites. Or that it is okay that a child only eats one-and-a-half meals on some days. Or that it if you wait long enough without resorting to coaxing, bribing, or begging, a child will eat what his body needs. And failing to be patient and instead making an issue of eating (or not eating), what began as a normal infant aversion to new tastes and textures can spiral into a divisive family catastrophe.

Are there some infants who are so hypersensitive to new tastes and textures that waiting will endanger their health? If they exist, in my experience they are very rare. However, there are certainly toddlers who have become hypersensitive. In my opinion, they were always vulnerable and would have been much less of a problem had they been properly managed early on when they were just a little neophobic.

Are there clues during the child’s infancy that his family is more likely to have significant difficulty making the transition from “feeding” to “presenting” food? This new study observed that high maternal anxiety was frequently observed in both moderate and severe selective-eating children. This is another example of how we need to be aware from a very early stage when a parent is anxious or depressed. The failure to identify and see that those issues are addressed can seriously impair the whole family’s wellness.

 

 

Finally, on the other end of the spectrum, is usual garden variety selective eating outgrown? Have you tried to host a dinner party lately? I don’t mean a pot luck supper – I’m talking about a sit-down meal with a single menu. My wife and I have almost given up trying. “Martha is gluten free (without a diagnosis), Bob is watching his cholesterol, Rachel is pretty sure she is lactose intolerant, and you know Charlie hates vegetables. The Wilsons only do organic and are vegetarians.”

Next time we are considering mailing them gift certificates for their favorite restaurants along with an invitation to come over to our place for an after dinner drink. BYOB.

Dr. Wilkoff practiced primary care pediatrics in Brunswick, Maine, for nearly 40 years. He has authored several books on behavioral pediatrics, including “Coping with a Picky Eater.”

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Bedtime (and/or) stories

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I’m not much of a reader. In fact, there was a 10-year period during which I wrote more books (four) than I read. In high school and college, I can’t recall ever finishing an assigned novel or play. I would read just enough to create the desired illusion. Even now that I have more time, I’m good for about 20 minutes before I have to put a book down and do something … anything. If my feet are level with my waist, four pages is my max before sleep overtakes me.

But I could be the poster boy for the value of reading to young children. My father was a great reader. At heart he was an actor, and I could listen to his theatrical voice read for hours. I was still being read to regularly until I was 8 or 9 years old. I am convinced that it was his gift for reading aloud when I was young that helped me develop a facility with language that was crucial to my academic successes. It certainly wasn’t my own reading.

Two recent studies have added to the growing body of evidence that reading to young children is critical to their later language development and success in school (“Home Reading Environment and Brain Activation in Preschool Children Listening to Stories,” by Hutton et al. [Pediatrics. 2015 Aug 10. pii: peds.2015-0359. Epub ahead of print] and “The Words Children Hear: Picture Books and the Statistics for Language Learning,” by Montag, Jones, and Smith [Psychol Sci. Aug 4, 2015. doi: 10.1177/0956797615594361. E-pub ahead of print]). Parents in your practice have probably not read either of these peer-reviewed studies, but they may have read the New York Times and an op-ed by pediatrician Perri Klass, in which she emphasizes the importance of reading (Bed Time Stories for Young Brains, August 17, 2015). They have received free books at your office and know that you recommend they read to their children every day.

Many of those parents who have bought into the value of reading also understand the importance of a good night’s sleep. But for some of those families, those two priorities can collide when it comes time for the warm and fuzzy tradition of reading a bedtime story.

Work schedules and other family obligations may have pushed their young child’s bedtime to the brink of and beyond a healthy hour. Adding a bedtime story – and we all know there is seldom just one story – will only compound the problem. Which is more important … a bedtime story or a healthy bedtime?

Of course if we are talking about a single isolated night, the answer is obvious … do both. But I’m talking about the family that is overbooked and always running late. On a “good” night, bedtime ritual for the 2-year-old may start at 7:30 p.m. Adding a story will push start time to a clearly unhealthy 8:00. As a physician long obsessed with the underappreciated and at times catastrophic effects of sleep deprivation, my answer would clearly be forget the bedtime story and turn off the light.

But families need not allow themselves to fall into situations that force such a binary decision of reading or not reading a bedtime story. In some cases, it is an adult-centered decision by one parent who selfishly expects his or her child to be kept up until the parent can be home to participate in the bedtime ritual. In other cases, instead of building the day’s schedule around a healthy bedtime, some families treat bedtime as an afterthought, something they will get to when they can get around to it.

In addition to enhancing a child’s language development, reading stories at bedtime can be a bonding and family-building activity. Reading also can be a calming ingredient and a sleep-enhancing component in an effective bedtime ritual. And for the child who resists bedtime, reading can be used a reward that can be withheld or increased as the situation requires.

While I sense that the practice of saying one’s prayers at bedtime has fallen out of fashion for many families, the bedtime story is alive and well. We must help remind parents that the bedtime is at least as important as the story.

Dr. Wilkoff practiced primary care pediatrics in Brunswick, Maine, for nearly 40 years. He has authored several books on behavioral pediatrics, including “Coping with a Picky Eater” and “Is My Child Overtired?: The Sleep Solution for Raising Happier, Healthier Children.” Email him at pdnews@frontlinemedcom.com.

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I’m not much of a reader. In fact, there was a 10-year period during which I wrote more books (four) than I read. In high school and college, I can’t recall ever finishing an assigned novel or play. I would read just enough to create the desired illusion. Even now that I have more time, I’m good for about 20 minutes before I have to put a book down and do something … anything. If my feet are level with my waist, four pages is my max before sleep overtakes me.

But I could be the poster boy for the value of reading to young children. My father was a great reader. At heart he was an actor, and I could listen to his theatrical voice read for hours. I was still being read to regularly until I was 8 or 9 years old. I am convinced that it was his gift for reading aloud when I was young that helped me develop a facility with language that was crucial to my academic successes. It certainly wasn’t my own reading.

Two recent studies have added to the growing body of evidence that reading to young children is critical to their later language development and success in school (“Home Reading Environment and Brain Activation in Preschool Children Listening to Stories,” by Hutton et al. [Pediatrics. 2015 Aug 10. pii: peds.2015-0359. Epub ahead of print] and “The Words Children Hear: Picture Books and the Statistics for Language Learning,” by Montag, Jones, and Smith [Psychol Sci. Aug 4, 2015. doi: 10.1177/0956797615594361. E-pub ahead of print]). Parents in your practice have probably not read either of these peer-reviewed studies, but they may have read the New York Times and an op-ed by pediatrician Perri Klass, in which she emphasizes the importance of reading (Bed Time Stories for Young Brains, August 17, 2015). They have received free books at your office and know that you recommend they read to their children every day.

Many of those parents who have bought into the value of reading also understand the importance of a good night’s sleep. But for some of those families, those two priorities can collide when it comes time for the warm and fuzzy tradition of reading a bedtime story.

Work schedules and other family obligations may have pushed their young child’s bedtime to the brink of and beyond a healthy hour. Adding a bedtime story – and we all know there is seldom just one story – will only compound the problem. Which is more important … a bedtime story or a healthy bedtime?

Of course if we are talking about a single isolated night, the answer is obvious … do both. But I’m talking about the family that is overbooked and always running late. On a “good” night, bedtime ritual for the 2-year-old may start at 7:30 p.m. Adding a story will push start time to a clearly unhealthy 8:00. As a physician long obsessed with the underappreciated and at times catastrophic effects of sleep deprivation, my answer would clearly be forget the bedtime story and turn off the light.

But families need not allow themselves to fall into situations that force such a binary decision of reading or not reading a bedtime story. In some cases, it is an adult-centered decision by one parent who selfishly expects his or her child to be kept up until the parent can be home to participate in the bedtime ritual. In other cases, instead of building the day’s schedule around a healthy bedtime, some families treat bedtime as an afterthought, something they will get to when they can get around to it.

In addition to enhancing a child’s language development, reading stories at bedtime can be a bonding and family-building activity. Reading also can be a calming ingredient and a sleep-enhancing component in an effective bedtime ritual. And for the child who resists bedtime, reading can be used a reward that can be withheld or increased as the situation requires.

While I sense that the practice of saying one’s prayers at bedtime has fallen out of fashion for many families, the bedtime story is alive and well. We must help remind parents that the bedtime is at least as important as the story.

Dr. Wilkoff practiced primary care pediatrics in Brunswick, Maine, for nearly 40 years. He has authored several books on behavioral pediatrics, including “Coping with a Picky Eater” and “Is My Child Overtired?: The Sleep Solution for Raising Happier, Healthier Children.” Email him at pdnews@frontlinemedcom.com.

I’m not much of a reader. In fact, there was a 10-year period during which I wrote more books (four) than I read. In high school and college, I can’t recall ever finishing an assigned novel or play. I would read just enough to create the desired illusion. Even now that I have more time, I’m good for about 20 minutes before I have to put a book down and do something … anything. If my feet are level with my waist, four pages is my max before sleep overtakes me.

But I could be the poster boy for the value of reading to young children. My father was a great reader. At heart he was an actor, and I could listen to his theatrical voice read for hours. I was still being read to regularly until I was 8 or 9 years old. I am convinced that it was his gift for reading aloud when I was young that helped me develop a facility with language that was crucial to my academic successes. It certainly wasn’t my own reading.

Two recent studies have added to the growing body of evidence that reading to young children is critical to their later language development and success in school (“Home Reading Environment and Brain Activation in Preschool Children Listening to Stories,” by Hutton et al. [Pediatrics. 2015 Aug 10. pii: peds.2015-0359. Epub ahead of print] and “The Words Children Hear: Picture Books and the Statistics for Language Learning,” by Montag, Jones, and Smith [Psychol Sci. Aug 4, 2015. doi: 10.1177/0956797615594361. E-pub ahead of print]). Parents in your practice have probably not read either of these peer-reviewed studies, but they may have read the New York Times and an op-ed by pediatrician Perri Klass, in which she emphasizes the importance of reading (Bed Time Stories for Young Brains, August 17, 2015). They have received free books at your office and know that you recommend they read to their children every day.

Many of those parents who have bought into the value of reading also understand the importance of a good night’s sleep. But for some of those families, those two priorities can collide when it comes time for the warm and fuzzy tradition of reading a bedtime story.

Work schedules and other family obligations may have pushed their young child’s bedtime to the brink of and beyond a healthy hour. Adding a bedtime story – and we all know there is seldom just one story – will only compound the problem. Which is more important … a bedtime story or a healthy bedtime?

Of course if we are talking about a single isolated night, the answer is obvious … do both. But I’m talking about the family that is overbooked and always running late. On a “good” night, bedtime ritual for the 2-year-old may start at 7:30 p.m. Adding a story will push start time to a clearly unhealthy 8:00. As a physician long obsessed with the underappreciated and at times catastrophic effects of sleep deprivation, my answer would clearly be forget the bedtime story and turn off the light.

But families need not allow themselves to fall into situations that force such a binary decision of reading or not reading a bedtime story. In some cases, it is an adult-centered decision by one parent who selfishly expects his or her child to be kept up until the parent can be home to participate in the bedtime ritual. In other cases, instead of building the day’s schedule around a healthy bedtime, some families treat bedtime as an afterthought, something they will get to when they can get around to it.

In addition to enhancing a child’s language development, reading stories at bedtime can be a bonding and family-building activity. Reading also can be a calming ingredient and a sleep-enhancing component in an effective bedtime ritual. And for the child who resists bedtime, reading can be used a reward that can be withheld or increased as the situation requires.

While I sense that the practice of saying one’s prayers at bedtime has fallen out of fashion for many families, the bedtime story is alive and well. We must help remind parents that the bedtime is at least as important as the story.

Dr. Wilkoff practiced primary care pediatrics in Brunswick, Maine, for nearly 40 years. He has authored several books on behavioral pediatrics, including “Coping with a Picky Eater” and “Is My Child Overtired?: The Sleep Solution for Raising Happier, Healthier Children.” Email him at pdnews@frontlinemedcom.com.

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Stage 0 Breast Cancer May Not Be the Strongest Indicator of Patient Mortality

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Stage 0 Breast Cancer May Not Be the Strongest Indicator of Patient Mortality
New research has emerged that shows treatment of ductal carcinoma in situ does not significantly affect mortality rates.

According to a study published today in JAMA Oncology, a diagnosis of ductal carcinoma in situ (DCIS)—or stage 0 breast cancer—may not be reason enough for treatment.

Researchers conducted a multivariate analysis of 108,196 women, whose data were pulled from the Surveillance, Epidemiology, and End Results (SEER) 18 registries database. The primary outcome of the study was 10- and 20-year cancer-specific mortality. The results showed that age at diagnosis and ethnicity were significant predictors of breast cancer mortality: Women diagnosed before age 35 had a higher risk of death from breast cancer at 20 years than did older women (7.8% vs 3.2%; hazard ratio [HR], 2.58; 95% confidence interval [CI], 1.85-3.60; P < .001), and black women had a higher risk of death from DCIS than did white, non-Hispanic women (7.0% vs 3.0%; adjusted HR, 2.42, 95% CI, 2.05-2.87; P < .001).

Related: Dividing to Conquer Breast Cancer

In addition, the article notes that the finding of greatest clinical importance was that prevention of ipsilateral invasive recurrence did not prevent death from breast cancer. Women diagnosed with DCIS who developed an ipsilateral invasive in-breast recurrence were 18.1 times more likely to die of breast cancer than were women who did not; however, after adjustment for tumor size, grade, and other factors, the difference in survival for mastectomy vs lumpectomy was not significant (HR, 1.20; 95% CI, 0.96-1.50; P = .11).

Patients with breast cancer often undergo the Oncotype DX breast cancer assay to identify those who are at low risk for death from breast cancer and who might not benefit from chemotherapy. However, the researchers of the current study propose that the test be used instead to identify patients who are at high risk for invasive recurrence.

Related: Advances in Targeted Therapy for Breast Cancer

The 10-year mortality rate assessed in this study continues a downward trend established in previous studies, but “it is unlikely that the decline in mortality [for women who received a diagnosis of ductal carcinoma in situ between 1998 and 2011] is due to more effective treatments,” the authors note, “because we show here that mortality rates did not vary with specific treatment.”

View on the News: Reboot needed on DCIS treatment

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Narod SA, Iqbal J, Giannakeas V, Sopik V, Sun P. JAMA Oncol. [Published online ahead of print August 20, 2015.]
doi: 10.1001/jamaoncol.2015.2510.

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New research has emerged that shows treatment of ductal carcinoma in situ does not significantly affect mortality rates.
New research has emerged that shows treatment of ductal carcinoma in situ does not significantly affect mortality rates.

According to a study published today in JAMA Oncology, a diagnosis of ductal carcinoma in situ (DCIS)—or stage 0 breast cancer—may not be reason enough for treatment.

Researchers conducted a multivariate analysis of 108,196 women, whose data were pulled from the Surveillance, Epidemiology, and End Results (SEER) 18 registries database. The primary outcome of the study was 10- and 20-year cancer-specific mortality. The results showed that age at diagnosis and ethnicity were significant predictors of breast cancer mortality: Women diagnosed before age 35 had a higher risk of death from breast cancer at 20 years than did older women (7.8% vs 3.2%; hazard ratio [HR], 2.58; 95% confidence interval [CI], 1.85-3.60; P < .001), and black women had a higher risk of death from DCIS than did white, non-Hispanic women (7.0% vs 3.0%; adjusted HR, 2.42, 95% CI, 2.05-2.87; P < .001).

Related: Dividing to Conquer Breast Cancer

In addition, the article notes that the finding of greatest clinical importance was that prevention of ipsilateral invasive recurrence did not prevent death from breast cancer. Women diagnosed with DCIS who developed an ipsilateral invasive in-breast recurrence were 18.1 times more likely to die of breast cancer than were women who did not; however, after adjustment for tumor size, grade, and other factors, the difference in survival for mastectomy vs lumpectomy was not significant (HR, 1.20; 95% CI, 0.96-1.50; P = .11).

Patients with breast cancer often undergo the Oncotype DX breast cancer assay to identify those who are at low risk for death from breast cancer and who might not benefit from chemotherapy. However, the researchers of the current study propose that the test be used instead to identify patients who are at high risk for invasive recurrence.

Related: Advances in Targeted Therapy for Breast Cancer

The 10-year mortality rate assessed in this study continues a downward trend established in previous studies, but “it is unlikely that the decline in mortality [for women who received a diagnosis of ductal carcinoma in situ between 1998 and 2011] is due to more effective treatments,” the authors note, “because we show here that mortality rates did not vary with specific treatment.”

View on the News: Reboot needed on DCIS treatment

Source
Narod SA, Iqbal J, Giannakeas V, Sopik V, Sun P. JAMA Oncol. [Published online ahead of print August 20, 2015.]
doi: 10.1001/jamaoncol.2015.2510.

According to a study published today in JAMA Oncology, a diagnosis of ductal carcinoma in situ (DCIS)—or stage 0 breast cancer—may not be reason enough for treatment.

Researchers conducted a multivariate analysis of 108,196 women, whose data were pulled from the Surveillance, Epidemiology, and End Results (SEER) 18 registries database. The primary outcome of the study was 10- and 20-year cancer-specific mortality. The results showed that age at diagnosis and ethnicity were significant predictors of breast cancer mortality: Women diagnosed before age 35 had a higher risk of death from breast cancer at 20 years than did older women (7.8% vs 3.2%; hazard ratio [HR], 2.58; 95% confidence interval [CI], 1.85-3.60; P < .001), and black women had a higher risk of death from DCIS than did white, non-Hispanic women (7.0% vs 3.0%; adjusted HR, 2.42, 95% CI, 2.05-2.87; P < .001).

Related: Dividing to Conquer Breast Cancer

In addition, the article notes that the finding of greatest clinical importance was that prevention of ipsilateral invasive recurrence did not prevent death from breast cancer. Women diagnosed with DCIS who developed an ipsilateral invasive in-breast recurrence were 18.1 times more likely to die of breast cancer than were women who did not; however, after adjustment for tumor size, grade, and other factors, the difference in survival for mastectomy vs lumpectomy was not significant (HR, 1.20; 95% CI, 0.96-1.50; P = .11).

Patients with breast cancer often undergo the Oncotype DX breast cancer assay to identify those who are at low risk for death from breast cancer and who might not benefit from chemotherapy. However, the researchers of the current study propose that the test be used instead to identify patients who are at high risk for invasive recurrence.

Related: Advances in Targeted Therapy for Breast Cancer

The 10-year mortality rate assessed in this study continues a downward trend established in previous studies, but “it is unlikely that the decline in mortality [for women who received a diagnosis of ductal carcinoma in situ between 1998 and 2011] is due to more effective treatments,” the authors note, “because we show here that mortality rates did not vary with specific treatment.”

View on the News: Reboot needed on DCIS treatment

Source
Narod SA, Iqbal J, Giannakeas V, Sopik V, Sun P. JAMA Oncol. [Published online ahead of print August 20, 2015.]
doi: 10.1001/jamaoncol.2015.2510.

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Assess heart disease risk with online calculators

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About half of all Americans have at least one of the three leading risk factors for heart disease: high blood pressure, high low-density lipoprotein cholesterol, and a history of smoking. It is important to keep track of heart disease risks, both potential and real.

Online calculators can be very useful for patients concerned about their heart health. Many such calculators, such as this one from the Mayo Clinic, look at your general risk for heart disease and make recommendations as to lifestyle changes to reduce risk. But there are also calculators focused on specific conditions, such as coronary heart disease, heart attack, and stroke.

Remember that calculators are not a replacement for a real diagnosis. If you suspect you have heart disease, be sure to see a doctor, and if something serious occurs, a visit to the emergency department is certainly valid.

Find more heart disease risk calculators here.

lfranki@frontlinemedcom.com

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About half of all Americans have at least one of the three leading risk factors for heart disease: high blood pressure, high low-density lipoprotein cholesterol, and a history of smoking. It is important to keep track of heart disease risks, both potential and real.

Online calculators can be very useful for patients concerned about their heart health. Many such calculators, such as this one from the Mayo Clinic, look at your general risk for heart disease and make recommendations as to lifestyle changes to reduce risk. But there are also calculators focused on specific conditions, such as coronary heart disease, heart attack, and stroke.

Remember that calculators are not a replacement for a real diagnosis. If you suspect you have heart disease, be sure to see a doctor, and if something serious occurs, a visit to the emergency department is certainly valid.

Find more heart disease risk calculators here.

lfranki@frontlinemedcom.com

About half of all Americans have at least one of the three leading risk factors for heart disease: high blood pressure, high low-density lipoprotein cholesterol, and a history of smoking. It is important to keep track of heart disease risks, both potential and real.

Online calculators can be very useful for patients concerned about their heart health. Many such calculators, such as this one from the Mayo Clinic, look at your general risk for heart disease and make recommendations as to lifestyle changes to reduce risk. But there are also calculators focused on specific conditions, such as coronary heart disease, heart attack, and stroke.

Remember that calculators are not a replacement for a real diagnosis. If you suspect you have heart disease, be sure to see a doctor, and if something serious occurs, a visit to the emergency department is certainly valid.

Find more heart disease risk calculators here.

lfranki@frontlinemedcom.com

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